CSE327

CSE327

Computer Vision

3

Dimitris Samaras (currently taught by ESE dept)

Introduces fundamental concepts, algorithms, and computational techniques in visual information processing. Covers image formation, image sensing, binary image analysis, image segmentation, Fourier image analysis, edge detection, reflectance map, photometric stereo, basic photogrammetry, stereo, pattern classification, extended Gaussian images, and the study of human visual system from an information processing point of view.

This course is offered as both CSE 327 and ESE 358.

CSE 114; ESE 218 or the discontinued ESE 318

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)

http://www.cs.sunysb.edu/~cse327