EEAP 431: Digital Image Processing

Spring 1997, Prof. Frank Merat

General Information

Course Instructor: Frank Merat, flm at po.cwru.edu, Glennan 518, x4572

 

Required Text

• Rafael Gonzalez and Paul Wintz, Digital Image Processing. Addison-Wesley, 1992. ISBN:0-20-150803-6.
  Digital Image Processing 1/e is out of print now but you can buy it used starting for $9.50 from Amazon.

This course was taught jointly with EBME 512 (Prof. David Wilson) so you will find some references and materials from that class in these notes.

Syllabus

• Syllabus (PDF, 20k)

Lecture Notes

• Image Processing Overview Slide show which illustrates basic image processing and what can be done with image processing. (PDF, 500kB)
• MATLAB Image Processing Toolbox Basic MATLAB programming, image definitions, basic image operations, example programs (PDF, 1.4 MB)
• Image transformations Binary images, thresholding, histograms, intensity transformations, connected components, geometric transformations (PDF, 632kB)
• Geometric transformations Homogeneous coordinates, compound transformations, perspective transformations, general geometric transformations, image warping, (PDF, 5.5 MB)
• Camera calibration Camera coordinate transformations,camera calibration (PDF, 3.5 MB)
• Spatial filtering Gray level transformations, histogram equatization, arithmetic operations, averaging, filter masks, smoothing and sharpening filters, edge operators, Laplacian, gradient, general edge operators (PDF, 1.7 MB)
• Morphological image processing Binary morphological operations, gray scale morphology, conditional dilation, geodesic dilation, watershed operations. (PDF, 5.9MB)
• Color image processing Color vision, color representations, color representation conversion, color image enhancement, color matching, CIE chromaticity diagram. (PDF, 956 kB)
• Edge segmentation Edge thresholding, edge relaxation, boundary tracing, graph searching, dynamic programming, Hough transform, deformable models. (PDF, 1.9MB)
• Region based segmentation Image thresholding: automatic, iterative, and adaptive; optimal thresholding; labeling; connectivity and connectedness; quadtrees and graphs; region splitting and merging. (PDF, 1.5MB)
• Deformable models Segmentation with locally deformable models, method of calculation, SCR approach, global models and segmentation. (PDF, 2MB)

References

• Dana H. Ballard and Christopher M. Brown Computer Vision. Prentice-Hall, 1982. ISBN:0-13-165316-4.
  This book is long out of print but gives a good overview of a computer science perspective of digtial image processing as applied to computer vision.
• Berthold Klaus Paul Horn Robot Vision. McGraw-Hill, 1986. ISBN:0-07-030349-5.
  This book gives a computer science perspective of machine vision methods applied to the real world.