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.
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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 Jean Gallier - arXiv
These are notes on the method of normalized graph cuts and its applications to graph clustering. I provide a thorough treatment of this deeply original method, including complete proofs. The main thrust of this paper is the method of normalized cuts.
by Asim Bhatti - InTech
The book comprehensively covers almost all aspects of stereo vision. In addition reader can find topics from defining knowledge gaps to the state of the art algorithms as well as current application trends of stereo vision.
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.