Course Details
Subject {L-T-P / C} : EC6673 : Computer Vision Laboratory { 0-0-3 / 2}
Subject Nature : Practical
Coordinator : Prof. Sukadev Meher
Syllabus
1. To get familiarized with MATLAB image processing toolbox
2. To study various pixel-wise transformations and histogram equalization
3. To implement de-noising and de-blurring algorithms in spatial domain
4. To implement de-noising and de-blurring algorithms in frequency domain
5. Spatial and frequency domain filtering for color images
6. Image segmentation using global thresholding
7. K-means clustering based segmentation
8. Classifier design with PCA
9. Classifier design with Neural Network
10. Mini-project
Course Objectives
- To perform basic pre-processing tasks like: histogram equalization and filtering
- To develop segmentation and classification algorithms
- To design classifiers
- To solve a real-life problem (mini-project)
Course Outcomes
After completion of this course, a student will be able: <br />1) To design basic image filters <br />2) To design and analyze efficient segmentation schemes <br />3) To design and analyze object classifiers <br />4) To analyze a real-life problem (e.g. face recognition) and find suitable solutions <br />5) To carry out research in the field of computer vision.
Essential Reading
- David A. Forsyth and Jean Ponce, Computer Vision: A Modern Approach, Pearson Education , 2008
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Supplementary Reading
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