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 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.
by Adrian Horridge - ANU E Press
The book is the only account of what the bee actually detects with its eyes. The erratic path to understanding makes interesting reading for anyone with an analytical mind who thinks about the methods of science or the engineering of seeing machines.
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.