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by Milan Sonka (Author), Vaclav Hlavac (Author), Roger Boyle (Author)
Image Processing, Analysis and Machine Vision represent an exciting part of modern cognitive and computer science. Following an explosion of inter- est during the Seventies, the Eighties were characterized by the maturing of the field and the significant growth of active applications; Remote Sensing, Technical Diagnostics, Autonomous Vehicle Guidance and Medical Imaging are the most rapidly developing areas. This progress can be seen in an in- creasing number of software and hardware products on the market as well as in a number of digital image processing and machine vision courses offered at universities world-wide. There are many texts available in the areas we cover - most (indeed, all of which we know) are referenced somewhere in this book. The subject suffers, however, from a shortage of texts at the 'elementary' level - that appropriate for undergraduates beginning or completing their studies of the topic, or for Master's students - and the very rapid developments that have taken and are still taking place, which quickly age some of the very good text books produced over the last decade or so. This book reflects the authors' experience in teaching one and two semester undergraduate and graduate courses in Digital Image Processing, Digital Image Analysis, Machine Vision, Pattern Recognition and Intelligent Robotics at their respective institutions.
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Vision allows humans to perceive and understand the world surrounding them; computer vision aims to duplicate human vision by electronically perceiving and understanding an image. Image Processing, Analysis and Machine Vision is a comprehensive introduction to the field providing up-to-date coverage of all aspects of the subject. This book reflects the authors' experience in teaching one and two semester undergraduate and graduate courses in Digital Image Processing, Digital Image Analysis, Machine Vision and Intelligent Robotics, it is also influenced by their active research in these area. Many algorithms, diagrams, examples and up-to-date references make this book required reading for students and professionals involved in computer vision.
