Syllabus

1. To get familiarized with basic functions available in Image Processing Toolbox of MATLAB/Python/open-CV.
2. To perform pixel-wise transforms, implement contrast adjustment of an image, Histogram processing and equalization.
3. To design image denoising filters in spatial domain for suppressing additive, multiplicative and impulsive noise
4. To study the performance of Ideal, Butterworth and Gaussian low pass and high pass filter
5. To perform image transforms (DCT, Wavelet)
6. To perform edge detection, line detection and corner detection techniques in images.
7. To perform/implement image segmentation algorithms
8. To perform morphological operations in images
9. Utilization of SIFT and HOG etc. feature descriptors for image analysis.
10. Object detection and recognition on available online image datasets
11. Motion estimation, optical flow computation and tracking
12. Mini project on Detection/Classification

To familiarize students with the implementation in MATLAB, Python of the basic image processing techniques and developing image processing algorithms

To familiarize students with the implementation of above tools for Computer Vision Applications.

CO1: Demonstrate on broad range of fundamental image processing techniques and algorithms (filtering, denoising, deblurring etc.)

CO2: Demonstrate on broad range of image analysis techniques and algorithms (edge detection, segmentation, morphological operators etc.)

CO3: Understand and implement the algorithms for robust image description, representation, image alignment and matching.

CO4: Understand and implement the algorithms for object/scene recognition, tracking, classification from images.

CO5: Identify, demonstrate and apply their knowledge by analyzing computer vision problems and employing (or proposing) effective solutions for various applications

R. C. Gonzalez, R. E. Woods, S. L. Eddins, Digital Image Processing using MATLAB, Prentice Hall

J. R. Parker, Algorithms for Image Processing and Computer Vision, Wiley and Sons

T. Morris, Computer Vision and Image Processing, Palgrave McMillan

1. IEEE Transaction on Pattern Analysis and Machine Intelligence
2. IEEE conference on Computer Vision & Pattern Recognition