ME 6406 Machine Vision

Credit Hours:	3-0-3
Prerequisite:	Graduate Standing in engineering or related discipline
Catalog Description:	Design of algorithms for vision systems for manufacturing, farming, construction, and the service industries. Image processing, optics, illumination, feature representation.
Textbook:	David A. Forsyth and Jean Ponce, Computer Vision: A Modern Approach, 1st Edition, Pearson Education, 2002
Instructor:	Kok-Meng Lee (Fall 2004)

Topics:

Introduction to machine vision concepts
Image Formation (image model and imaging devices)
Vision signal processing, acquisition, and conversation
Image enhancement
Histogram-modification
Image filter and smoothing
Image Segmentation
Labeling
Gradient operator and detection of discontinuity (point, line, edge)
Hough transform method for curve detection
Graphic theoretic technique
Edge linking and boundary detection
Region-growing segmentation
Morphological processing
Feature and boundary representation
Model based pattern matching
Geometric transformation, camera model, parameter and coordinate calibration
Motion, optical flow and image sequences
Machine vision design case studies
(electronics, illumination and structure light, reflectance and color, geometrical optics, algorithms)

Mode of Lecture

Instruction:

Evaluation: 4 assignments (10% each); 1 in-class quiz (20%); Final Examination (40%)

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Revised June 2004