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Practical algorithms for image analysis: description, examples, and code Lawrence O'Gorman, Michael J. Sammon, Michael Seul
Publisher: Cambridge University Press

The only somewhat negative is that examples are for openCV 1.1. Topics: Digitization, processing, segmentation, projection, data structures, binary images, contour filling, thinning, curve fitting, surface fitting, 2-D graphics, polygon clipping, 3-D graphics. I thought it might be a fun challenge to work through the book in Flash and Actionscript, not by just porting over the existing code examples, but by analyzing the text and coming up with my own implementation from scratch. Drawing on their long experience as users and developers of image analysis algorithms and software, the authors present a practical description and implementation of the most suitable procedures. The book has basic algorithms for many standard image processing tasks. Practical Algorithms for Image Analysis Descriptions Examples and Code 299 pages | English | ISBN: 0521660653 | 15 April 2000 | DJVU | 30.93 MB ? PolySpace products use sophisticated math and analysis to prove the absence of run-time errors without the need to compile and run the code. Practical Algorithms for Image Analysis (Book 2000) - Goodreads Practical Algorithms for Image Analysis: Description, Examples, and Code [With CDROM] Practical Algorithms for Image Analysis with CD-ROM / Edition 2. Each self-contained section I appreciated the book set-up: each section describes one single task, describes the problem, gives an example, discusses a solution given in literature, and presents the input / output / options for the C code. Click on image to see enlarged view. Buy Practical Algorithms for Image Analysis with CD-ROM: Description, Examples, and Code Book Reviews - This book offers guided access to a collection of algorithms. Each self-contained section projects for classroom use. And now the accompanying CD-ROM contains C programs not only as source code for carrying out the book's procedures but also as executables with a graphical user interface for Windows and Linux. The simplest and most widely used technique in Diffusion MRI is called Diffusion Tensor Imaging (DTI). I wanted to try the same sort of analysis that a researcher working in my field might want to use. Each section The accompanying CD-ROM features C programs not only as source code for carrying out the procedures, but also as executables with a graphical user interface for Windows and Linux. I often find myself writing small functions that help visualize certain image processing algorithms. Drawing on their long experience as users and developers of image analysis algorithms and software, the authors present a description and implementation of the most suitable procedures in easy-to-use form. Simple color-coding to show code verification results.