Offered Every Fall

Credit Hours: 3-0-3
Prerequisites: 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.
Textbooks: David A. Forsyth and Jean Ponce, Computer Vision: A Modern Approach, 1st Edition, Pearson Education, 2002
Instructors: Kok-Meng Lee
  • 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)
Grading Scheme (%):



In class quiz


Final Group Project