Computer Vision: Algorithms and Applications
by Richard Szeliski
Publisher: Springer 2010
Number of pages: 655
The book emphasizes basic techniques that work under real-world conditions, not the esoteric mathematics that has intrinsic elegance but less practical applicability. The text is suitable for teaching a senior-level undergraduate course in computer vision to students in computer science and electrical engineering.
Home page url
Download or read it online for free here:
by Xenophon Papademetris - Image Processing and Analysis Group
The author's goal was to provide sufficient introductory material for a typical 1st year engineering graduate student with some background in programming in C and C++ to leverage modern open source toolkits in medical image analysis.
by Simon J.D. Prince - Cambridge University Press
This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use data to learn the relationships between the observed image data and the aspects that we wish to estimate.
by Peng-Yeng Yin - IN-TECH
The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms.
by Kokichi Sugihara - The MIT Press
The book on computer vision which solves the problem of the interpretation of line drawings and answers many other questions regarding the errors in the placement of lines in the images. Sugihara presents a mechanism that mimics human perception.