Machine Vision: Automated Visual Inspection and Robot Vision
by David Vernon
Publisher: Prentice Hall 1991
Number of pages: 260
Machine vision is a multidisciplinary subject, utilizing techniques drawn from optics, electronics, mechanical engineering, computer science, and artificial intelligence. This book is an introduction to Machine Vision which will allow the reader quickly to comprehend the essentials of this fascinating topic. Emphasis will be placed on the fundamental tools for image acquisition, processing, and analysis; a range of techniques, dealing with very simple two dimensional systems, through more sophisticated two-dimensional approaches, to the three-dimensional robot vision, will be explained in some detail.
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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 Xenophon Papademetris - Image Processing and Analysis Group
The author's goal was to provide sufficient introductory material for a typical 1st year engineering graduate student with some background in programming in C and C++ to leverage modern open source toolkits in medical image analysis.
by Simon J.D. Prince - Cambridge University Press
This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use data to learn the relationships between the observed image data and the aspects that we wish to estimate.
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