by R. Jain, R. Kasturi, B. G. Schunck
Publisher: McGraw-Hill 1995
Number of pages: 549
This text is intended to provide a balanced introduction to machine vision. Basic concepts are introduced with only essential mathematical elements. The details to allow implementation and use of vision algorithm in practical application are provided, and engineering aspects of techniques are emphasized. This text intentionally omits theories of machine vision that do not have sufficient practical applications at the time.
Home page url
Download or read it online for free here:
(multiple PDF files)
by Aapo Hyvarinen, Jarmo Hurri, Patrik O. Hoyer - Springer
Introductory textbook and a research monograph on modelling the statistical structure of natural images. The statistical structure of natural images is described using a number of statistical models whose parameters are estimated from image samples.
by Asim Bhatti (ed.) - InTech
The topics covered in this book include fundamental theoretical aspects of robust stereo correspondence estimation, novel and robust algorithms, hardware implementation for fast execution, neuromorphic engineering, probabilistic analysis, 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 Widodo Budiharto - Science Publishing Group
This book is written to provide an introduction to intelligent robotics using OpenCV. It is intended for a first course in robot vision and covers modeling and implementation of intelligent robot. Written for student and hobbyist.