In order to provide our readers with as many resources on imaging and machine vision as possible, Andy Wilson, Vision Systems Design Editor in Chief, has compiled a list of educational and informative books on various imaging topics that he personally recommends. Check out this week’s recommendations here:
- Pattern Recognition and Machine Learning by Christopher Bishop: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed.
- Texture Analysis in Machine Vision Hardcoverby M. K. Pietikainen: Texture analysis is an important generic research area of machine vision. The potential areas of application include biomedical image analysis, industrial inspection, analysis of satellite or aerial imagery, content-based retrieval from image databases, document analysis, biometric person authentication, scene analysis for robot navigation, texture synthesis for computer graphics and animation, and image coding.
- Computer Vision for Human-Machine Interaction by Roberto Cipolla, Alex Pentland: Recent advances in the field of computer vision are leading to novel and radical changes in the way we interact with computers. It will soon be possible to enable a computer linked to a video camera to detect the presence of users, track faces, arms and hands in real time, and analyze expressions and gestures. The implications for interface design are immense and are expected to have major repercussions for all areas where computers are used, from the work place to recreation.
- Machine Learning and Image Interpretation (Advances in Computer Vision and Machine Intelligence)by Terry Caelli, Walter F. Bischof: In this groundbreaking new volume, computer researchers discuss the development of technologies and specific systems that can interpret data with respect to domain knowledge. Although the chapters each illuminate different aspects of image interpretation, all utilize a common approach - one that asserts such interpretation must involve perceptual learning in terms of automated knowledge acquisition and application, as well as feedback and consistency checks between encoding, feature extraction, and the known knowledge structures in a given application domain.
- Vision Interface: Real World Applications of Computer Vision (Machine Perception and Artificial Intelligence)by Mohamed Cheriet, Yee Hong Yang: This volume contains selected papers presented at Vision Interface 1998, held in Vancouver, Canada, in June 1998. It spans a wide spectrum of topics in computer vision and image processing. The field of computer vision and image processing has grown at a phenomenal rate due to the development of innovative techniques coupled with the advance in hardware that have been made available at lower cost.
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