Computer Image Processing And Recognition

Computer Image Processing and Recognition

Proceedings of the 2019 International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV'19) held July 29th - August 1st, 2019 in Las Vegas, Nevada.

This book presents a collection of high-quality research papers accepted to multi-conference consisting of International Conference on Image Processing and Communications (IP&C 2021), International Conference on Computer Recognition Systems (CORES 2021), International Conference on Advanced Computer Systems (ACS 2021) held jointly in Bydgoszcz, Poland (virtually), in June 2021. The accepted papers address current computer science and computer systems-related technological challenges and solutions, as well as many practical applications and results. The first part of the book deals with advances in pattern recognition and classifiers, the second part is devoted to image processing and computer vision, while the third part addresses practical applications of computer recognition systems. Machine learning solutions for security and networks are tackled in part four of the book, while the last part collects papers on progress in advanced computer systems. We believe this book will be interesting for researchers and practitioners in many fields of computer science and IT applications.

Computer Vision and Image Processing contains review papers from the Computer Vision, Graphics, and Image Processing volume covering a large variety of vision-related topics. Organized into five parts encompassing 26 chapters, the book covers topics on image-level operations and architectures; image representation and recognition; and three-dimensional imaging. The introductory part of this book is concerned with the end-to-end performance of image gathering and processing for high-resolution edge detection. It proposes methods using mathematical morphology to provide a complete edge detection process that may be used with any slope approximating operator. This part also discusses the automatic control of low-level robot vision, presents an image partitioning method suited for parallel implementation, and describes invariant architectures for low-level vision. The subsequent two sections present significant topics on image representation and recognition. Topics covered include the use of the primitives chain code; the geometric properties of the generalized cone; efficient rendering and structural-statistical character recognition algorithms; multi-level thresholding for image segmentation; knowledge-based object recognition system; and shape decomposition method based on perceptual structure. The fourth part describes a rule-based expert system for recovering three-dimensional shape and orientation. A procedure of intensity-guided range sensing to gain insights on the concept of cooperative-and-iterative strategy is also presented in this part. The concluding part contains supplementary texts on texture segmentation using topographic labels and an improved algorithm for labeling connected components in a binary image. Additional algorithms for three-dimensional motion parameter determination and surface tracking in three-dimensional binary images are also provided.

This book delivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science, medical imaging, or wherever the study of identification and classification of objects by electronics-driven image processing and pattern recognition is relevant. Object analysis first uses image processing to detect objects and extract their features, then identifies and classifies them by pattern recognition. Its manifold applications include recognition of objects in satellite images which enable discrimination between different objects, such as fishing boats, merchant ships or warships; machine spare parts e.g. screws, nuts etc. (engineering); detection of cancers, ulcers, tumours and so on (medicine); and recognition of soil particles of different types (agriculture or soil mechanics in civil engineering). Outlines the identification and classification of objects by electronics-driven image processing and pattern recognition Discusses object detection, shape, roundness and sharpness analysis, orientation analysis and arrangement analysis Delivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science and medical imaging

Interest in computer vision and image processing has grown in recent years with the advancement of everyday technologies such as smartphones, computer games, and social robotics. These advancements have allowed for advanced algorithms that have improved the processing capabilities of these technologies. Advancements in Computer Vision and Image Processing is a critical scholarly resource that explores the impact of new technologies on computer vision and image processing methods in everyday life. Featuring coverage on a wide range of topics including 3D visual localization, cellular automata-based structures, and eye and face recognition, this book is geared toward academicians, technology professionals, engineers, students, and researchers seeking current research on the development of sophisticated algorithms to process images and videos in real time.

This book is designed for undergraduate and postgraduate students of Computer Science and Engineering, Information Technology, Electronics and Communication Engineering, and Electrical Engineering. The book comprehensively covers all the important topics in digital image processing and pattern recognition along with the fundamental concepts, mathematical preliminaries and theoretical derivations of significant theorems. The image processing topics include coverage of image formation, digitization, lower level processing, image analysis, image compression, and so on. The topics on pattern recognition include statistical decision making, decision tree learning, artificial neural networks, clustering and others. An application of simulated annealing for edge detection is described in an appendix. The book is profusely illustrated with more than 200 figures and sketches as an added feature. KEY FEATURES: Provides a large number of worked examples to strengthen the grasp of the concepts. Lays considerable emphasis on the algorithms in order to teach students how to write good practical programs for problem solving. Devotes a separate chapter to currently used image format standards. Offers problems at the end of each chapter to help students test their understanding of the fundamentals of the subject.

A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.