Introduction to Programming for Image Analysis with VTK
by Xenophon Papademetris
Publisher: Image Processing and Analysis Group 2006
Number of pages: 238
This book is an edited collection of class handouts that I wrote for the graduate seminar "Programming for Medical Image Analysis" that was taught at Yale University, Department of Biomedical Engineering, in the Fall of 2006. My goal for the class was to provide sufficient introductory material for a typical 1st year engineering graduate student with some background in programming in C and C++ to acquire the skills to leverage modern open source toolkits in medical image analysis and visualization such as the Visualization Toolkit (VTK) and, to a lesser extent, the Insight Toolkit (ITK).
Home page url
Download or read it online for free here:
by David Vernon - Prentice Hall
This book is a comprehensive introduction to machine vision, it will allow the reader to quickly comprehend the essentials of this topic. Emphasis is on a range of the tools and techniques for image acquisition, processing, and analysis.
by Julio Ponce, Adem Karahoca - IN-TECH
Nearest feature classification for face recognition, subspace methods, a multi-stage classifier for face recognition undertaken by coarse-to-fine strategy, PCA-ANN face recognition system based on photometric normalization techniques, etc.
by Scott Krig - Springer
Provides an extensive survey of over 100 machine vision methods, with a detailed taxonomy for local, regional and global features. It provides background to develop intuition about why interest point detectors and feature descriptors actually work.
by Richard Szeliski - Springer
The book emphasizes basic techniques that work under real-world conditions, not the esoteric mathematics without practical applicability. The text is suitable for a senior-level undergraduates in computer science and electrical engineering.