21-12-2012, 01:11 PM
Multimedia Signal Processing Lab
[attachment=44702]
Overview
The multimedia signal processing laboratory was established with a definite purpose and clear understanding. We needed a signal processing lab which will cater research interests and will complement teaching & learning methodology. The mission is to lead the mind towards visualizing concepts and reduce the clutter in the thought process thereby paving way to true knowledge.
This lab is managed by the signal processing group which consists of faculty with good research background and enthusiastic and motivated students. Experiments are included based mostly on audio signal processing. With time, efforts will be made to design experiments to include other media signals such as image and video as part of the curriculum. Open ended experiments have been appended to pique interest in students.
This lab introduces students to Multimedia Signal Processing (MSP) design and analysis techniques that are core knowledge for Signal Processing engineers, and which serve as solid grounding for advanced level work in MSP. The lab aims at achieving the following objectives:
1. To emphasize the teaching of key Audio Signal Processing concepts, such as overview of discrete time signal and systems in time domain & frequency domain, wavelet decomposition and reconstruction of audio signals, perform different types of scaling on audio, computation of Fast Fourier transform and its implementation.
2. To give students an introduction to real-time MSP requirements by exposing them to the real time challenges in audio, video and image signal processing, which will help them get acquainted with the programming using MATLAB®.
3. To heighten students' awareness of the vast array of diverse practical MSP applications by exposing them to some practical MSP demos and operations involved in this area.
Laboratory Experiments (MTE121 & MET121)
1. Write a MATLAB program to load, display, and play back Audio files.
2. Handling Audio files in MATLAB.
a. Read an audio file, its sampling rate and bits per sample.
b. Write an audio file, at different sampling rates, at different bits per sample. c. Play an audio file at different sampling rates.
d. Use of whos command to view the variables in the workspace.
3. Up-sampling and down-sampling of audio file and its effect in perceptual properties.
4. Fourier Transform and inverse Fourier Transform of Audio signals, plot of the spectrum of audio signals. Audio synthesis from a select number (subset) of FFT components.
5. For an audio signal, include a framing module in a program and set the frame size to 256
sample. Every frame should be read in a 256 × 1 real vector called. Compute the fast Fourier transform of this vector. Compute the magnitude of the complex vector Sfreq and plot its magnitude in dB up to the fold-over frequency. This computation should be part of the frame-by-frame audio processing program.
6. Analysis of audio signals using Short-term Fourier Transform (STFT) in the Time- frequency domain.
7. Analysis of multi-resolution, wavelet decomposition and reconstruction of audio signals at different levels using different filters.
8. Write a program to plot the absolute threshold of hearing in quiet. Give a plot in terms of a linear Hz scale.
9. Power spectral density of different types of audio signals.
10. Insert and recover data from an audio signal using LSB coding method
11. Write a MATLAB program to load, display, and play back Video files.
12. Handling Video files in MATLAB.
a. Read a Video file, its sampling rate and bits per sample.
b. Write a Video file, at different sampling rates, at different bits per sample.
c. Play a Video file at different sampling rates.
Future Research Areas
1. Multimodal Biometrics.
2. Biometric Template protection methods.
3. Medical Image watermarking.
4. Watermarking of Biometric data.
5. Blind Source separation of audio signals.
Lab Infrastructure and Computing facility
1. Computers- Dual Core 4 GB RAM latest computers.
2. Laptops for Portable biometric data collection.
3. MATLAB – Software.
4. Finger Print Scanner (500dpi) Model: Digital Persona U areU4500
5. Finger Print SDK software compatible with the scanner.
6. Iris Camera for Capture, process & recognition. Iris capture near IR Sensitive Camera with Optics, Lighting and Stand.
7. Iris capture and process frame grabber with SDK.
[attachment=44702]
Overview
The multimedia signal processing laboratory was established with a definite purpose and clear understanding. We needed a signal processing lab which will cater research interests and will complement teaching & learning methodology. The mission is to lead the mind towards visualizing concepts and reduce the clutter in the thought process thereby paving way to true knowledge.
This lab is managed by the signal processing group which consists of faculty with good research background and enthusiastic and motivated students. Experiments are included based mostly on audio signal processing. With time, efforts will be made to design experiments to include other media signals such as image and video as part of the curriculum. Open ended experiments have been appended to pique interest in students.
This lab introduces students to Multimedia Signal Processing (MSP) design and analysis techniques that are core knowledge for Signal Processing engineers, and which serve as solid grounding for advanced level work in MSP. The lab aims at achieving the following objectives:
1. To emphasize the teaching of key Audio Signal Processing concepts, such as overview of discrete time signal and systems in time domain & frequency domain, wavelet decomposition and reconstruction of audio signals, perform different types of scaling on audio, computation of Fast Fourier transform and its implementation.
2. To give students an introduction to real-time MSP requirements by exposing them to the real time challenges in audio, video and image signal processing, which will help them get acquainted with the programming using MATLAB®.
3. To heighten students' awareness of the vast array of diverse practical MSP applications by exposing them to some practical MSP demos and operations involved in this area.
Laboratory Experiments (MTE121 & MET121)
1. Write a MATLAB program to load, display, and play back Audio files.
2. Handling Audio files in MATLAB.
a. Read an audio file, its sampling rate and bits per sample.
b. Write an audio file, at different sampling rates, at different bits per sample. c. Play an audio file at different sampling rates.
d. Use of whos command to view the variables in the workspace.
3. Up-sampling and down-sampling of audio file and its effect in perceptual properties.
4. Fourier Transform and inverse Fourier Transform of Audio signals, plot of the spectrum of audio signals. Audio synthesis from a select number (subset) of FFT components.
5. For an audio signal, include a framing module in a program and set the frame size to 256
sample. Every frame should be read in a 256 × 1 real vector called. Compute the fast Fourier transform of this vector. Compute the magnitude of the complex vector Sfreq and plot its magnitude in dB up to the fold-over frequency. This computation should be part of the frame-by-frame audio processing program.
6. Analysis of audio signals using Short-term Fourier Transform (STFT) in the Time- frequency domain.
7. Analysis of multi-resolution, wavelet decomposition and reconstruction of audio signals at different levels using different filters.
8. Write a program to plot the absolute threshold of hearing in quiet. Give a plot in terms of a linear Hz scale.
9. Power spectral density of different types of audio signals.
10. Insert and recover data from an audio signal using LSB coding method
11. Write a MATLAB program to load, display, and play back Video files.
12. Handling Video files in MATLAB.
a. Read a Video file, its sampling rate and bits per sample.
b. Write a Video file, at different sampling rates, at different bits per sample.
c. Play a Video file at different sampling rates.
Future Research Areas
1. Multimodal Biometrics.
2. Biometric Template protection methods.
3. Medical Image watermarking.
4. Watermarking of Biometric data.
5. Blind Source separation of audio signals.
Lab Infrastructure and Computing facility
1. Computers- Dual Core 4 GB RAM latest computers.
2. Laptops for Portable biometric data collection.
3. MATLAB – Software.
4. Finger Print Scanner (500dpi) Model: Digital Persona U areU4500
5. Finger Print SDK software compatible with the scanner.
6. Iris Camera for Capture, process & recognition. Iris capture near IR Sensitive Camera with Optics, Lighting and Stand.
7. Iris capture and process frame grabber with SDK.