Cellular Automata In Image Processing And Geometry
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Cellular Automata in Image Processing and Geometry
The book presents findings, views and ideas on what exact problems of image processing, pattern recognition and generation can be efficiently solved by cellular automata architectures. This volume provides a convenient collection in this area, in which publications are otherwise widely scattered throughout the literature. The topics covered include image compression and resizing; skeletonization, erosion and dilation; convex hull computation, edge detection and segmentation; forgery detection and content based retrieval; and pattern generation. The book advances the theory of image processing, pattern recognition and generation as well as the design of efficient algorithms and hardware for parallel image processing and analysis. It is aimed at computer scientists, software programmers, electronic engineers, mathematicians and physicists, and at everyone who studies or develops cellular automaton algorithms and tools for image processing and analysis, or develops novel architectures and implementations of massive parallel computing devices. The book will provide attractive reading for a general audience because it has do-it-yourself appeal: all the computer experiments presented within it can be implemented with minimal knowledge of programming. The simplicity yet substantial functionality of the cellular automaton approach, and the transparency of the algorithms proposed, makes the text ideal supplementary reading for courses on image processing, parallel computing, automata theory and applications.
Advancements in Computer Vision and Image Processing
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.
Applications of Evolutionary Computation
Author: Pablo García-Sánchez
language: en
Publisher: Springer Nature
Release Date: 2025-04-23
This two-volume set, LNCS 15612 and 15613 constitutes the refereed proceedings of the 28th European Conference on Applications of Evolutionary Computation, EvoApplications 2025, held as part of EvoStar 2025, in Trieste, Italy, during April 23–25, 2025, and co-located with the EvoStar events, EvoCOP, EvoMUSART, and EuroGP. The 50 full papers and 18 short papers presented in this book were carefully reviewed and selected from 104 submissions. These papers have been organized in the following topical sections: Part I: EvoApplications. Part II: Evolutionary machine learning; 30 years of particle swarm optimisation; Analysis of Evolutionary Computation Methods: Theory, Empirics, and Real-World Applications; Bio-inspired Algorithms for Green Computing and Sustainable Complex Systems; Computational Intelligence for Sustainability; EvoLLMs (Integrating Evolutionary Computing with Large Language Models (LLMs); Evolutionary Computation in Edge, Fog, and Cloud Computing; Evolutionary Computation in Image Analysis, Signal Processing, and Pattern Recognition; Machine Learning and AI in Digital Healthcare and Personalized Medicine; Soft Computing Applied to Games.