Today, much of everyday-life information is represented visually and processed digitally. Digital imaging is ubiquitous, with applications including photography, television, movies, tomography, printing, robot perception, surveillance, and many more. This is an undergraduate-level introductory course to the fundamentals of computer vision and digital image processing. We expect to cover topics including light and color, image formation, image pyramid, filtering, warping, mosaics, alignment and tracking, stereo vision, and machine learning based face and object recognition.
- Implementation of canny edge detection, image blending using gaussian filters
- Hough Transform, Hough Lines and Segements
- 2D to 3D Stereo
- Creating mosaic image from multiple images
The task is to find a topic to implement CV methods. Our topic is the automatic detection of license plates of cars.