This package provides a practical approach to the study of image processing, image analysis and pattern matching by using a PC-based software package called Vision Assistant. A library of compressed images is used to illustrate the manipulation and analysis of pictures and offers the reader a guide to effectively using the 78 image processing functions and a non-mathematical treatment of the theory of image processing and analysis. It provides readers with an effective way to study the potential of image processing in the fields of office automation, multi-media computer systems, automation and quality control and medical imaging. This package runs on any IBM compatible PC (needs 386 or higher), and is supplied on 3 1/2" disk only. This book should be of interest to professionals and advanced students in computer science, electronics engineering, biomedical engineering, arts and design, medical electronics specialists.
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Introduction to image processing. Camera technologies. The nature of digitised images. The image analysis computer system. How images are processed. Statistical pattern classifiers. The integrated recognition environment. References. Vision assistant. Introduction. Installation of vision assistant. The menu system. The enhancement menu. Summary. Exercises. References. Feature extraction. The detection menu. Detection menu functions. Summary on edge operators. Exercises on edge operators. Edge post processing. Region growing. References. The analysis menu. Introduction to image analysis methods. Binary shape detection and coding. Internal features of objects. Measurements used in vision assistant. Definitions of measurement parameters. Exercises on chain coding. The analyse menu functions. Interactive chain coding. References. The display screen. Introduction to the display screen. The edge detect sub-menu. The analyse menu. Exercises on the use of the display menu. The logic sub-menu. Summary. The describe menu. Introduction to the description of image features. The describe menu. Exercises using the describe menu. Classifications using the task list menu. Definitions of feature vectors. Exercises on object classification. References. Questions and answers. Introduction to examples. Image enhancement problems and solutions. Object detection problems and solutions. References. Index. Appendices.
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