Modern Metaheuristics in Image Processing

This book explores the use of metaheuristic algorithms (MA) in image processing, presenting the most prominent MA from 2019 and 2020 and discussing their application in various tasks such as segmentation, shape identification, and object detection. It includes detailed explanations, tuning parameters, and examples with different datasets. The book also conducts experiments and statistical analysis to evaluate the performance of the MA. Additionally, it discusses future research opportunities and open questions in the field.

Format: Hardback
Length: 132 pages
Publication date: 28 September 2022
Publisher: Taylor & Francis Ltd

The use of metaheuristic algorithms (MA) has surged in recent years, extending their application beyond traditional fields. In the past two years, a significant number of MA have emerged as viable alternatives for tackling complex optimization problems. This comprehensive book presents a collection of the most prominent MA from 2019 and 2020, showcasing their utilization in image processing tasks. Additionally, a comprehensive literature review of MA and digital image processing is provided as an introductory guide. Each algorithm is thoroughly explained, with a special emphasis on tuning parameters and proper implementation for image processing applications. Numerous examples are provided to allow readers to explore and validate the effectiveness of these intelligent methods. Given the widespread use of image processing across diverse domains, this book considers a variety of datasets, including magnetic resonance images, thermal images, agriculture images, and more. By presenting these diverse datasets, readers gain insights into potential implementation strategies that complement the theoretical explanations presented.

In addressing image processing problems, this book focuses on segmentation using various metrics based on entropies or variances. Similarly, chapters cover the identification of different shapes and the detection of objects, providing comprehensive coverage of these important aspects. Each chapter is complemented with extensive experimental results and statistical analysis, allowing readers to evaluate the performance of the MA. Furthermore, a section is included that discusses key findings, conclusions, and open questions for further research. This section serves as a valuable resource for the audience, encouraging them to delve deeper into the field of MA and image processing.

Weight: 272g
Dimension: 145 x 223 x 14 (mm)
ISBN-13: 9781032019772