by Dana H. Ballard, Christopher M. Brown
Publisher: Prentice Hall 1982
Number of pages: 539
Computer vision is the construction of explicit, meaningful descriptions of physical objects from images. Image understanding is very different from image processing, which studies image-to-image transformations, not explicit description building. Descriptions are a prerequisite for recognizing, manipulating, and thinking about objects. Parts of the book assume some mathematical and computing background (calculus, linear algebra, data structures, numerical methods). However, throughout the book mathematical rigor takes a backseat to concepts. Our intent is to transmit a set of ideas about a new field to the widest possible audience.
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by S. Dance, Z.Q. Liu, T.M. Caelli - World Scientific
Explores a method for symbolically intrepreting images based upon a parallel implementation of a network-of-frames to describe intelligent processing. The system has been implemented in an object-oriented environment in the language Parlog++.
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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 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.
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The main ideas in the area of face recognition are security applications and human-computer interaction. The goal of this book is to provide the reader with the most up to date research performed in automatic face recognition.