Aims and Scope

The aim of the symposium is to bring together researchers in the exciting and dynamic area of image and signal processing and computer vision and to foster exchange of new ideas.

Topics of interest include but are not limited to:

A. Image and Video Processing
A1. Image enhancement
A2. Image noise filtering
A3. Image representation and transforms
A4. Image restoration
A5. Multiresolution processing and wavelets
A6. Morphological image processing
A7. Color image processing
A8. Interpolation and geometric transformations

B. Image and Video Analysis
B1. Image segmentation
B2. Motion analysis
B3. Neural networks and fuzzy processing
B4. Image and video databases
B5. Content-based image retrieval
B6. Computer and machine vision
B7. Pattern recognition
B8. Knowledge-based vision

C. Image Formation and Reproduction
C1. Image formation
C2. Imaging techniques
C3. Sampling and quantization
C4. Scanning
C5. Color reproduction and halftoning
C6. Volume and surface rendering
C7. Display systems and printing
C8. Image quality assessment

D. Signal Processing
D1. Analog and digital signal processing
D2. Signal representation and transforms
D3. Statistical signal processing
D4. Filter design
D5. Multirate and wavelet signal processing
D6. Coding techniques
D7. Adaptive signal processing
D8. Multidimensional signal processing

E. Signal Analysis
E1. Time-frequency signal analysis
E2. Signal modeling, prediction and identification
E3. System identification
E4. Statistical signal analysis
E5. Sampling and compressive sampling
E6. Biomedical signal analysis
E7. Speech recognition
E8. Design and implementation of DSP systems

F. Applications
F1. Biomedical signal and image processing
F2. Biomedical imaging
F3. Biometrics signal and image processing
F4. Genomic signal processing
F5. Watermarking and information hiding
F6. Bioinformatics
F7. Communication signal processing
F8. Information forensics and security
F9. Multimedia and speech/language processing
F10. Acoustic and vibration signal processing
F11. Signal processing for sensor networks