CS 7367:Machine Vision

3 Class Hours 0 Laboratory Hours 3 Credit Hours
Prerequisite: Students should possess basic proficiency in programming and data structures as well as a basic familiarity with Linear Algebra; CS 3304 or CS 5040 (or equivalent).
This course introduces students to basic concepts and techniques in machine vision. Students successfully completing this course will be able to apply a variety of computer techniques for the design and analysis of efficient algorithms for real-world applications, such as optical character recognition, face detection and recognition, motion estimation, human tracking, and gesture recognition. The topics covered include Geometric Camera Models, image enhancement, edge detection, image transformation, feature extraction, image segmentation, object detection, object recognition, tracking, gesture recognition, image formation and camera models, video analysis and stereo vision. The course will be evaluated based on programming assignments, written tests, and a final term project.