By: Tim Bower

Kansas State University Salina

Machine Vision Study Guide

This study guide is available from timbower.us.

This study guide is made available by the Creative Commons Attribution 3.0 United States License.

This Machine Vision Study Guide provides notes and information for the Machine Vision (CMST 357) course offered by K–State Salina, which is the campus of Kansas State University located in Salina, Kansas. Self study of the material in the Study Guide is welcome.

Announcements

• Remember that you can find the study guide by entering timbower.us into your web browser.
• Additional resources are available on K-State Online.
• This online study guide is intended to only provide a few supplemental notes. It is not the textbook.

Contents:

• 1. Introduction to Machine Vision
  • 1.1. Weekly Schedule
  • 1.2. What is Machine Vision
  • 1.3. Applications of Machine Vision
  • 1.4. Environment
• 2. Commercial Vision Systems
  • 2.1. What can they do?
  • 2.2. Why study machine vision algorithms?
• 3. Digital Images
  • 3.1. Summary
• 4. MATLAB Basics
• 5. MATLAB Toolboxes
  • 5.1. MathWork’s IPT
  • 5.2. MVTB
• 6. Image Histograms
• 7. Arithmetic Operations
  • 7.1. Monadic Operations
  • 7.2. Diadic Operations
• 8. Geometric Operations
  • 8.1. Rotating a Pixel
  • 8.2. Transformation Matrix
• 9. Color Images
  • 9.1. Chromaticity Coordinates
  • 9.2. HSV Colorspace
• 10. Image Formation
  • 10.1. Cameras
  • 10.2. Perspective Projection Model
  • 10.3. Homography
  • 10.4. Stereo Cameras
  • 10.5. Active 3D Sensors
• 11. Neighborhood (Spatial) Processing
  • 11.1. Convolution and Correlation
  • 11.2. Median Filter
• 12. Morphology
• 13. Segmentation
  • 13.1. Thresholding
  • 13.2. Finding Blobs
• 14. Image Features
  • 14.1. Moments
  • 14.2. Equivalent Ellipse
  • 14.3. Circularity
  • 14.4. Filtering Blobs
• 15. Edge Detection
  • 15.1. Hough Transform
• 16. Visual Servoing
• 17. Frequency Domain Filtering
  • 17.1. Fourier Series
  • 17.2. The Complex Exponential Basis Function
  • 17.3. Continuous 1D Fourier Transform
  • 17.4. Discrete 1D Fourier Transform
  • 17.5. Discrete 2D Fourier Transform of Images
  • 17.6. FFT Agorithm
  • 17.7. Other Fourier Transform Properties
  • 17.8. Frequency Domain Filters
• 18. Glossary
• 19. Home Work and Lab Assignments
• 20. Bibliography

Indices and tables

• Index
• Module Index
• Search Page