Picture Processing By Computer

The rapid rate at which the field of digital picture processing has grown in the past five years had necessitated extensive revisions and the introduction of topics not found in the original edition.

The text has been prepared for researchers involved in picture processing. It is designed to help them in mastering the methods at the professional level. From the viewpoint of both signal theory and information theory, the treatment covers the basic principles of the digital methods for the processing of continuous signals such as picture signals. In addition, it reviews schemes for correcting signal distortion in imaging systems, for the enhancement of picture contrast, and for the automatic measurement of picture details. The text contains new results on digital filtering and transformation, and a new approach to picture processing. The main applications, as documented by numerous examples, are in space research, remote sensing, medical diag nostics, nondestructive testing. The material has been tested extensively in class-room use with students of both computer science and electrical engineering at the senior undergraduate and the first-year graduate level. The present edition is not a translation of the original Russian book, but it has been extended substantially as well as updated. The author is grate ful to Dr. H. Lotsch of Springer-Verlag for his proposal to prepare this text and for many helpful suggestions. He likes to thank Dr. P. Hawkes for a careful copy-editing of the manuscript, and acknowledges numerous criti cal comments by Professors S.L. Gorelik, T.S. Huang, A.W. Lohmann,and A.M. Trakhtman.

Across three volumes, the Handbook of Image Processing and Computer Vision presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The authoritative insights presented within cover all aspects of the sensory subsystem required by an intelligent system to perceive the environment and act autonomously. Volume 1 (From Energy to Image) examines the formation, properties, and enhancement of a digital image. Topics and features: • Describes the fundamental processes in the field of artificial vision that enable the formation of digital images from light energy • Covers light propagation, color perception, optical systems, and the analog-to-digital conversion of the signal • Discusses the information recorded in a digital image, and the image processing algorithms that can improve the visual qualities of the image • Reviews boundary extraction algorithms, key linear and geometric transformations, and techniques for image restoration • Presents a selection of different image segmentation algorithms, and of widely-used algorithms for the automatic detection of points of interest • Examines important algorithms for object recognition, texture analysis, 3D reconstruction, motion analysis, and camera calibration • Provides an introduction to four significant types of neural network, namely RBF, SOM, Hopfield, and deep neural networks This all-encompassing survey offers a complete reference for all students, researchers, and practitioners involved in developing intelligent machine vision systems. The work is also an invaluable resource for professionals within the IT/software and electronics industries involved in machine vision, imaging, and artificial intelligence. Dr. Cosimo Distante is a Research Scientist in Computer Vision and Pattern Recognition in the Institute of Applied Sciences and Intelligent Systems (ISAI) at the Italian National Research Council (CNR). Dr. Arcangelo Distante is a researcher and the former Director of the Institute of Intelligent Systems for Automation (ISSIA) at the CNR. His research interests are in the fields of Computer Vision, Pattern Recognition, Machine Learning, and Neural Computation.

The report consists of several parts of a forthcoming book on Digital Picture Processing, dealing with pictures and their computer representation; image enhancement; and picture matching. (Author).

The focus of this book is on providing a thorough treatment of image processing with an emphasis on those aspects most used in computer graphics. Throughout, the authors concentrate on describing and analysing the underlying concepts rather than on presenting algorithms or pseudocode. As befits a modern introduction to this topic, a healthy balance is struck between discussing the underlying mathematics of the subject and the main topics covered: signal processing, data discretization, the theory of colour and different colour systems, operations in images, dithering and half-toning, warping and morphing, and image processing.

Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the link between theory and exemplar code of the algorithms." Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation. The only text to concentrate on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods A thorough overview of available feature extraction methods including essential background theory, shape methods, texture and deep learning Up to date coverage of interest point detection, feature extraction and description and image representation (including frequency domain and colour) Good balance between providing a mathematical background and practical implementation Detailed and explanatory of algorithms in MATLAB and Python