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Nano Scientific Research Centre Pvt Ltd
Nano Scientific Research Centre Pvt Ltd


MATLAB - SIGNAL PROCESSING IEEE PROJECTS



An Optimal Data Hiding Scheme with Tree- Based Parity Check

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An Optimal Data Hiding Scheme with Tree- Based Parity Check
Approx. Rs 10,000 / student
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1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

3. FFT-based Frequency Offset Estimation in OFDM Systems.

4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

6. MATLAB Implementation of Image Segmentation Algorithms.

7. Image Enhancement via Adaptive Un sharp Masking.

8. Speech compression using LPC and wavelet.

9. Image Thumbnails That Represent Blur and Noise.

10. Learning color and locality cues for moving object detection and segmentation.

11. Application of Matlab in Moving Object Detecting Algorithm

12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

13. A Color Image Segmentation algorithm Based on Region Growing.

14. Detecting Abandoned ObjectsWith aMoving

15. Face Detection using Combined Skin Color Detector and Template Matching Method.

16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

17. A Generalized Unsharp Masking Algorithm.

18. License Plate Localisation based on Morphological Operations.

19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

 

 

20. Video shot boundary detection using motion activity descriptor.

  • Minimum Order Quantity: 1 student
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    Two-Way Amplify Forward Relaying Using Frequency

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    Two-Way Amplify Forward Relaying Using Frequency
    Approx. Rs 10,000 / student
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    Frequency-domain oversampling (FDO) is studied for twoway amplified-and-forward relaying (TWAR) on the frequency-selective fading channel. In the FDO-based scheme, a zero postfix (ZP) is inserted in the transmitted data block, and a fractionally spaced frequency-domain (FSFD) minimum mean-square-error (MMSE) estimate is performed on the received data block. Compared with the conventional MMSE receiver using a cyclic prefix (CP) without FDO, the FSFD -MMSE receiver can extract the frequency diversity on the frequency-selective fading channel. Moreover, a semi-analytical result on the error performance of the FSFD-MMSE receiver is also provided, which matches the simulation result closely. Finally, the robustness of the FDO-based scheme to the timevarying fading and the frequency offset is also studied through simulations.

  • Minimum Order Quantity: 1 student
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    Fine Granularity And Spatially- Adaptive Regularization

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    Fine Granularity And Spatially- Adaptive Regularization
    Approx. Rs 10,000 / student
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    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

    20. Video shot boundary detection using motion activity descriptor.

     

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    Adaptive Lattice Reduction Over Correlated Fading Channels

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    Adaptive Lattice Reduction Over Correlated Fading Channels
    Approx. Rs 10,000 / student
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    Abstract:

    In multiple-input multiple-output (MIMO) systems, lattice reduction significantly improves the performance of approximate detection techniques. Taking advantage of the temporal correlation of a Rayleigh fading channel, low complexity lattice reduction is investigated in this work by adaptively updating the reduced lattice basis. We show that a careful use of previous channel realizations yields a significant saving in complexity with a minimal degradation in performance.

     

    Existing system:

    In point to point MIMO systems, decoding represents a challenging problem. Recently, some of the methods from lattice theory are used as solutions to this problem where MIMO detection can be formulated as a closest lattice point search (CLPS). The complexity of using lattice reduction in a lattice reduction aided detection method can be ignored in a quasi-static scenario where the channel is considered fixed for the whole transmission frame which makes it possible to use the same result for quite a large number of received signals.

    Disadvantages of existing system:

    · Decoding algorithm is complicated

    · High complexity

     

     

    Proposed system:

    The proposed adaptive methods can be used in conjugation with any lattice reduction algorithm and in any multi-antenna scenario over correlated channels that requires lattice reduction such as MIMO detection and broadcast pre coding.

    Advantages of proposed system :

    Ø Low complexity

    Ø Ml decoding algorithm is used

    Ø Low BER

    Domain

    Communication

    Wireless communication is the transfer of information over a distance without the use of electrical conductors or "wires". The distances involved may be short (a few meters as in television remote control) or long (thousands or millions of kilometers for radio communications). When the context is clear, the term is often shortened to "wireless". Wireless communication is generally considered to be a branch of telecommunications.

  • Minimum Order Quantity: 1 student
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    Interference Cancellation and Detection

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    Interference Cancellation and Detection
    Approx. Rs 10,000 / student
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    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

    20. Video shot boundary detection using motion activity descriptor.

    Abstract:

    In multiple access channels, when users know each other’s channels, precoders can be designed utilizing channel information to cancel the interference at the receiver without sacrificing the diversity or the complexity of the system. Recently, it was shown that when there are only two users,a receiver can completely cancel the interference of the two users and provide full diversity for each user. Unfortunately, the scheme only works for two users. In this paper, we extend the scheme to more than 2 users. In other words, we propose a system to achieve interference cancellation and full diversity with low complexity for any number of users. Then, we extend the results to any number of users with any number of transmit and receive antennas. Our main idea is to design precoders, using the channel information, to make it possible for different users to transmit over orthogonal directions. Then, using the orthogonality of the transmitted signals, the receiver can separate them and decode the signals independently. We also analytically prove that our system provides full diversity to each user. Simulation results confirm our analytical proof and show that our proposed scheme outperforms other existing interference cancellation schemes.

     

    Disadvantages of existing system:

    Ø High complexity

    Ø High interference

    Ø Limited users

    Proposed system:

    Our main idea is to design precoders, using the channel information, to make it possible for different users to transmit over orthogonal directions. Then, using the orthogonality of the transmitted signals, the receiver can separate them and decode the signals independently. We have analytically proved that the system provides full diversity to each user and extended the results to any number of users each with any number of transmit antennas and one receiver with any number of receive antennas.

     

     

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    Space Time Block Coded Spatial Modulation

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    Space Time Block Coded Spatial Modulation
    Approx. Rs 10,000 / student
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    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

     

     

    20. Video shot boundary detection using motion activity descriptor.

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    A Generalized Unsharp Masking Algorithm

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    A Generalized Unsharp Masking Algorithm
    Approx. Rs 10,000 / student
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    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

     

     

    20. Video shot boundary detection using motion activity descriptor.

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    Real Time Projects On Dip 2015

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    Real Time Projects On Dip 2015
    Approx. Rs 10,000 / student
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    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

     

     

    20. Video shot boundary detection using motion activity descriptor.

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    An Efficient Video Segmentation Algorithm

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    An Efficient Video Segmentation Algorithm
    Approx. Rs 10,000 / student
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    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

     

     

    20. Video shot boundary detection using motion activity descriptor.

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    Efficient Detection Ordering Scheme

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    Efficient Detection Ordering Scheme
    Approx. Rs 10,000 / student
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    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned Objects With aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

     

     

    20. Video shot boundary detection using motion activity descriptor.

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    FFT Based Frequency Offset Estimation In OFDM Systems

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    FFT Based Frequency Offset Estimation In OFDM Systems
    Approx. Rs 10,000 / student
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    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

     

     

    20. Video shot boundary detection using motion activity descriptor.

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    Mobile Emitter Geo Location and Tracking

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    Mobile Emitter Geo Location and Tracking
    Approx. Rs 10,000
    Get Best Quote

    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

     

     

    20. Video shot boundary detection using motion activity descriptor.

    Yes! I am interested

    Copyright Protection Of Gray Scale Images By Watermarking

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    Copyright Protection Of Gray Scale Images By Watermarking
    Approx. Rs 10,000 / student
    Get Best Quote

    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

     

     

    20. Video shot boundary detection using motion activity descriptor.

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    MATLAB Implementation Of Image Segmentation Algorithms

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    MATLAB Implementation Of Image Segmentation Algorithms
    Approx. Rs 10,000 / student
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    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

    20. Video shot boundary detection using motion activity descriptor.

     

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    Image Enhancement Via Adaptive Un Sharp Masking

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    Image Enhancement Via Adaptive Un Sharp Masking
    Approx. Rs 10,000 / student
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    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

    20. Video shot boundary detection using motion activity descriptor.

     

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    Speech Compression Using LPC and Wavelet

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    Speech Compression Using LPC and Wavelet
    Approx. Rs 10,000 / student
    Get Best Quote

    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

    20. Video shot boundary detection using motion activity descriptor.

     

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    Image Thumbnails That Represent Blur and Noise

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    Image Thumbnails That Represent Blur and Noise
    Approx. Rs 10,000 / student
    Get Best Quote

    1. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique.

    2. Efficient Detection Ordering Scheme for MIMO Transmission Using Power Control.

    3. FFT-based Frequency Offset Estimation in OFDM Systems.

    4. Mobile Emitter Geo location and Tracking Using TDOA and FDOA Measurements.

    5. Copyright protection of Gray Scale Images by Watermarking Technique using (N, N) Secret Sharing Scheme.

    6. MATLAB Implementation of Image Segmentation Algorithms.

    7. Image Enhancement via Adaptive Un sharp Masking.

    8. Speech compression using LPC and wavelet.

    9. Image Thumbnails That Represent Blur and Noise.

    10. Learning color and locality cues for moving object detection and segmentation.

    11. Application of Matlab in Moving Object Detecting Algorithm

    12. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform.

    13. A Color Image Segmentation algorithm Based on Region Growing.

    14. Detecting Abandoned ObjectsWith aMoving

    15. Face Detection using Combined Skin Color Detector and Template Matching Method.

    16. HAIRIS: A Method for Automatic Image Registration through Histogram-Based Image Segmentation.

    17. A Generalized Unsharp Masking Algorithm.

    18. License Plate Localisation based on Morphological Operations.

    19. Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis.

    20. Video shot boundary detection using motion activity descriptor.

     

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    Time Domain Channel Estimation for OQAM-OFDM Systems: Algori

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    Time Domain Channel Estimation for OQAM-OFDM Systems: Algori
    Approx. Rs 10,000 / student
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    —In this paper, we first present a general time domain model for the channel estimation in the orthogonal frequency division multiplexing system with offset quadrature amplitude modulation (OQAM-OFDM), and utilize the frequency domain pilots to estimate the time domain channel impulse responses. Different form the conventional methods, there is no specific requirement for the length of the symbol interval compared to the the maximum channel delay spread in the proposed scheme. Furthermore, with the proposed time domain model, the channel statistic information could be utilized to improve the performance of the channel estimation. Then, we propose two channel estimation schemes, i.e., linear minimum mean square error (LMMSE) and weighted least square (WLS), and we also derive their corresponding Bayesian Cramér-Rao Bound (BCRB) and Cramér-Rao Bound (CRB) bounds, respectively. Simulation results demonstrate that the BCRB and CRB bounds could be achieved by the proposed LMMSE and WLS methods, respectively. Moreover, simulation results show that the proposed methods are much robust to the time synchronization error compared to the conventional frequency domain methods, and imply that the pulse shaping filter with waveforms concentrated in the time domain could be employed in OQAM-OFDM systems to improve the channel estimation performance and spectral efficiency.

  • Minimum Order Quantity: 1 student
  • Yes! I am interested

    Peak-to-Average Power Ratio Reduction for OFDM/OQAM Signals

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    Peak-to-Average Power Ratio Reduction for OFDM/OQAM Signals
    Approx. Rs 10,000 / student
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    In this paper, we consider the peak-to-average power ratio (PAPR) reduction problem for orthogonal frequency-division multiplexing with offset quadrature amplitude modulation (OFDM/OQAM). In particular, the OFDM/OQAM signal is generated by summing over M time-shifted OFDM/OQAM symbols, where successive symbols are interdependent with each other. The alternative-signal (AS) method, which directly leads to the independent AS (AS-I) and joint AS (AS-J) algorithms, is employed to reduce the PAPR of the OFDM/OQAM signal. The AS-I algorithm reduces the PAPR symbol by symbol with low complexity, whereas the AS-J algorithm applies optimal joint PAPR reduction among M OFDM/OQAM symbols with much higher complexity. To balance the performance and the computation complexity, we propose a sequential optimization procedure, which is denoted AS-S, which achieves a desired compromise between performance and complexity.

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    One-Shot Blind CFO and Channel Estimation for OFDM

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    One-Shot Blind CFO and Channel Estimation for OFDM
    Approx. Rs 10,000 / student
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    —In this paper, we design a new blind joint carrier frequency offset (CFO) and channel estimation method for orthogonal frequency-division multiplexing (OFDM) with multiantenna receiver. The proposed algorithm requires only one received OFDM block and thus belongs to the category of one-shot estimation methods. Other advantages of the proposed algorithm include 1) it supports fully loaded data carriers and is thus spectral effi- cient; 2) the channel from the transmitter to each receive antenna can be blindly estimated with only a scaling ambiguity; and 3) the algorithms outperforms the existing methods. Moreover, we derive the Cramér–Rao Bounds (CRB) of joint CFO and channel estimation in closed forms. Numeral results not only show the effectiveness of the proposed algorithm but also demonstrate its closed performance to CRB.

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    Multiple Source Localization in Wireless Sensor Networks Bas

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    Multiple Source Localization in Wireless Sensor Networks Bas
    Approx. Rs 10,000 / student
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    We investigate the localization of multiple signal sources based on sensors performing time-of-arrival (TOA) measurement in wireless sensor networks. Moving beyond the widely studied single source localization problem, concurrently active multiple sources substantially complicate the problem since anchored sensor nodes are unaware of associations between measured signals and source nodes. At the same time, as the total number of possible source-measurement associations grows exponentially with the number of sensor nodes, it is inefficient to attempt conventional single-source localization algorithm for each possible association in a brute-force manner. In this work, we address this difficult problem from a joint optimization perspective. Specifically, we consider simultaneous estimation of source-measurement associations and the source locations, in addition to finding the initial signal transmission time. This joint optimization problem includes both discrete and continuous variables. We propose an efficient three-step algorithm that progressively simplifies the original problem through convex relaxation and sensible approximations. Our proposed algorithm demonstrates results comparable to a genie-aided method that utilizes known source-measurement associations.

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    Multi-Stream Transmission for Highly Frequency Selective Cha

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    Multi-Stream Transmission for Highly Frequency Selective Cha
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    This paper addresses the joint design of MIMO precoding and decoding matrices for filter bank multicarrier (FBMC) systems based on OQAM, known as FBMC/OQAM. Existing solutions that support multi-stream transmission only give satisfactory performance in scenarios with high coherence bandwidth channels. To make progress towards the application of FBMC/OQAM to MIMO channels, we study the design of novel solutions that provide robustness against the channel frequency selectivity and support multi-stream transmission. To this end, two techniques have been devised under the criterion of minimizing the sum mean square error. The non-circular nature of the OQAM symbols has not been ignored, making evident the convenience of performing a widely linear processing. The first technique keeps the complexity at a reasonable level but in exchange the original problem is relaxed yielding a suboptimal solution. With the objective of performing closer to the optimum solution, the second option iteratively computes precoders and equalizers by resorting to an alternating optimization method, which is much more complex. We have demonstrated via simulations that the first technique nearly achieves the same results as the iterative design. Simulation results show that the proposed low-complexity solution outperforms existing MIMO-FBMC/OQAM schemes in terms of bit error rate. As for the comparison with OFDM, the numerical results highlight that FBMC/OQAM remains competitive, with and without perfect channel state information, while it provides spectral effi- ciency gains. Under highly frequency selective channels the proposed technique significantly outperforms OFDM.

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    Joint Approximately Sparse Channel Estimation and Data Detec

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    Joint Approximately Sparse Channel Estimation and Data Detec
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    It is well known that the impulse response of a wideband wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.

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    Group-Sparse Signal Denoising Non-Convex Regularization

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    Group-Sparse Signal Denoising Non-Convex Regularization
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    Convex optimization with sparsity-promoting convex regularization is a standard approach for estimating sparse signals in noise. In order to promote sparsity more strongly than convex regularization, it is also standard practice to employ non-convex optimization. In this paper, we take a third approach. We utilize a non-convex regularization term chosen such that the total cost function (consisting of data consistency and regularization terms) is convex. Therefore, sparsity is more strongly promoted than in the standard convex formulation, but without sacrificing the attractive aspects of convex optimization (unique minimum, robust algorithms, etc.). We use this idea to improve the recently developed ‘overlapping group shrinkage’ (OGS) algorithm for the denoising of group-sparse signals. The algorithm is applied to the problem of speech enhancement with favorable results in terms of both SNR and perceptual quality.

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    Performance Analysis of Linear-Equality-Constrained Least-Sq

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    Performance Analysis of Linear-Equality-Constrained Least-Sq
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    We analyze the performance of a linear-equality-constrained least-squares (CLS) algorithm and its relaxed version, called rCLS, that is obtained via the method of weighting. The rCLS algorithm solves an unconstrained least-squares problem that is augmented by incorporating a weighted form of the linear constraints. As a result, unlike the CLS algorithm, the rCLS algorithm is amenable to our approach to performance analysis presented here, which is akin to the energy-conservation-based methodology. Therefore, we initially inspect the convergence properties and evaluate the precision of estimation as well as satisfaction of the constraints for the rCLS algorithm in both mean and mean-square senses. Afterwards, we examine the performance of the CLS algorithm by evaluating the limiting performance of the rCLS algorithm as the relaxation parameter (weight) approaches infinity. Numerical examples verify the accuracy of the theoretical findings.

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    Compressive Imaging via Approximate Message Passing With Ima

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    Compressive Imaging via Approximate Message Passing With Ima
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    —We consider compressive imaging problems, where images are reconstructed from a reduced number of linear measurements. Our objective is to improve over existing compressive imaging algorithms in terms of both reconstruction error and runtime. To pursue our objective, we propose compressive imaging algorithms that employ the approximate message passing (AMP) framework. AMP is an iterative signal reconstruction algorithm that performs scalar denoising at each iteration; in order for AMP to reconstruct the original input signal well, a good denoiser must be used. We apply two wavelet-based image denoisers within AMP. The first denoiser is the “amplitude-scale-invariant Bayes estimator” (ABE), and the second is an adaptive Wiener filter; we call our AMP-based algorithms for compressive imaging AMP-ABE and AMP-Wiener. Numerical results show that both AMP-ABE and AMP-Wiener significantly improve over the state of the art in terms of runtime. In terms of reconstruction quality, AMP-Wiener offers lower mean-square error (MSE) than existing compressive imaging algorithms. In contrast, AMP-ABE has higher MSE, because ABE does not denoise as well as the adaptive Wiener filter.

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    Clutter Subspace Estimation in Low Rank Heterogeneous Noise

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    Clutter Subspace Estimation in Low Rank Heterogeneous Noise
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    This paper addresses the problem of the Clutter Subspace Projector (CSP) estimation in the context of a disturbance composed of a Low Rank (LR) heterogeneous clutter, modeled here by a Spherically Invariant Random Vector (SIRV), plus a white Gaussian noise (WGN). In such context, the corresponding LR adaptive filters and detectors require less training vectors than classical methods to reach equivalent performance. Unlike classical adaptive processes, which are based on an estimate of the noise Covariance Matrix (CM), the LR processes are based on a CSP estimate. This CSP estimate is usually derived from a Singular Value Decomposition (SVD) of the CM estimate. However, no Maximum Likelihood Estimator (MLE) of the CM has been derived for the considered disturbance model. In this paper, we introduce the fixed point equation that MLE of the CSP satisfies for a disturbance composed of a LR-SIRV clutter plus a zero mean WGN. A recursive algorithm is proposed to compute this solution. Numerical simulations validate the introduced estimator and illustrate its interest compared to the current state of art.
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    Adaptive Randomized Coordinate Descent for Sparse Systems: L

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    Adaptive Randomized Coordinate Descent for Sparse Systems: L
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    Coordinate descent (CD) is a simple optimization technique suited to low complexity requirements and also for solving large problems. In randomized version, CD was recently shown as very effective for solving least-squares (LS) and other optimization problems. We propose here an adaptive version of randomized coordinate descent (RCD) for finding sparse LS solutions, from which we derive two algorithms, one based on the lasso criterion, the other using a greedy technique. Both algorithms employ a novel way of adapting the probabilities for choosing the coordinates, based on a matching pursuit criterion. Another new feature is that, in the lasso algorithm, the penalty term values are built without knowing the noise level or using other prior information. The proposed algorithms use efficient computations and have a tunable trade-off between complexity and performance through the number of CD steps per time instant. Besides a general theoretical convergence analysis, we present simulations that show good practical behavior, comparable to or better than that of state of the art methods.
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    Turbo Processing for Speech Recognition

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    Turbo Processing for Speech Recognition
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    Speech recognition is a classic example of a human/machine interface, typifying many of the difficulties and opportunities of human/machine interaction. In this paper, speech recognition is used as an example of applying turbo processing principles to the general problem of human/machine interface. Speech recognizers frequently involve a model representing phonemic information at a local level, followed by a language model representing information at a nonlocal level. This structure is analogous to the local (e.g., equalizer) and nonlocal (e.g., error correction decoding) elements common in digital communications. Drawing from the analogy of turbo processing for digital communications, turbo speech processing iteratively feeds back the output of the language model to be used as prior probabilities for the phonemic model. This analogy is developed here, and the performance of this turbo model is characterized by using an artificial language model. Using turbo processing, the relative error rate improves significantly, especially in high-noise settings.

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    A Spatial Diffusion Strategy for Tap-Length Estimation Over

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    A Spatial Diffusion Strategy for Tap-Length Estimation Over
    Approx. Rs 8,000 / student
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    We consider the distributed estimation problem, where a set of nodes is required to collectively estimate some parameter vector of interest with unknown or variable tap-length. In practice, a sufficiently large filter length is utilized in such contexts to avoid a large excess mean square error at steady state, thereby resulting in slower convergence rate and increased computations. In this work we motivate and propose a new diffusion-based variable tap-length algorithm, which is able to track tap-length changes during the convergence process. Theoretical analyses are provided in terms of steady-state performance and convergence performance, which are verified by simulation results. Some general criteria for parameter selections are also given according to the performance analyses. Numerical simulations demonstrate the efficiency of the proposed algorithm as compared with existing techniques, and robustness to parameter settings provided the parameter choice guidelines are satisfied.
  • Minimum Order Quantity: 1 student
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