People Innovation Excellence

COMPUTER VISION (2/2 Credits)

Learning Outcomes:

On successful completion of this course, students will be able to: Describe the computational principles underlying various application of Computer Vision Systems; Understand the various standard procedures of image preprocessing prior to image analysis; Capable to identify and extract different image features required for various application of Computer Vision Systems; Capable of developing reliable and accurate Computer Vision Systems for solving various image based industrial problems.

Topics:

  1. Introduction to Computer Vision (CVS);
  2. Image Formation and Representation;
  3. Grayscale Transformations and Image Filtering (Spatial Domain);
  4. Grayscale Transformations and Image Filtering (Fequency Domain);
  5. Edge Detection;
  6. Feature Tracking and Binary Image Analysis;
  7. Image Segmentation (Part 01);
  8. Image Segmentation (Part 02);
  9. Stereo Correspondence;
  10. 3D Reconstruction;
  11. Structures From Motion;
  12. Recognition (Part 01);
  13. Recognition (Part 02).

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