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 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 R. Jain, R. Kasturi, B. G. Schunck - McGraw-Hill
The book 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.
by Jan Erik Solem - O'Reilly Media
The idea behind this book is to give an easily accessible entry point to hands-on computer vision with enough understanding of the underlying theory and algorithms to be a foundation for students, researchers and enthusiasts.
by Joachim Weickert - Teubner
Many recent techniques for digital image enhancement and multiscale image representations are based on nonlinear PDEs. This book gives an introduction to the main ideas behind these methods, and it describes in a systematic way their foundations.