Introduces fundamental concepts, algorithms, and techniques in visual information processing. Covers image formation, binary image processing, image features, model fitting, optics, illumination, texture, motion, segmentation, and object recognition.

CSE 214 or 230; AMS 210 or MAT 211

• Introduce the fundamental concepts and computational techniques in visual information processing.
• Present algorithms for understanding images and video, such as segmentation, edge detection, and reflectance analysis.

• Computer Vision by Stockman & Shapiro

• Students should demonstrate a basic ability to design and develop computational algorithms and implement them for the following applications:automatic inspection and measurement based on binary image processing (two-dimensional machine vision).
• Gray-level image processing and analysis techniques (e.g. image segmentation, edge detection, image filtering, curve fitting).
• Three-dimensional shape recovery through stereo image analysis.
• Object recognition based on feature vector classification and template matching.

• Image processing: mask-based filtering, median filtering, subsampling, edge-detection (2 weeks)
• Feature detection, Morphing and Mosaicing images (2 weeks)
• Stereo Reconstruction (2 weeks)
• Final project. Select from suggested topcs (4 weeks)