This book includes original research findings in the field of memetic algorithms for image processing applications. It gathers contributions on theory, case studies, and design methods pertaining to memetic algorithms for image processing applications ranging from defence, medical image processing, and surveillance, to computer vision, robotics, etc. The content presented here provides new directions for future research from both theoretical and practical viewpoints, and will spur further advances in the field.

Focuses on memetic algorithms and recent advances pertaining to image processing applications Shares both theoretical and practical perspectives Will benefit researchers, professionals, practitioners and students alike

Autorentext

Dr. D. Jude Hemanth received his B.E. degree in ECE from Bharathiar University in 2002, M.E. degree in communication systems from Anna University in 2006, and Ph.D. from Karunya University in 2013. His research areas include computational intelligence and image processing. He has authored more than 100 research papers in reputed international journals, as well as one book (with VDM Verlag, Germany) and numerous book chapters with major publishers such as Springer and Inderscience. He has served as an associate editor of IEEE Access Journal. He is also a guest editor for many journals with Springer, Inderscience, IOS Press, etc. A member of the IEEE Technical Committee on Neural Networks (IEEE Computational Intelligence Society) and IEEE Technical Committee on Soft Computing (IEEE Systems, Man and Cybernetics Society), he has completed one funded research project for the CSIR, Government of India. Currently, he is working as an Associate Professor at the Department of ECE, Karunya University, Coimbatore, India. 

B. Vinoth Kumar received the B.E. degree in Electronics and Communication Engineering from the Periyar University in 2003, and the ME and Ph.D. degrees in Computer Science and Engineering from the Anna University in 2009 and 2016, respectively. He is an Associate Professor with 15 years of experience at PSG College of Technology. His current research interests include Computational Intelligence, Memetic Algorithms, and Image Processing. He has established an Artificial Intelligence Research (AIR) Laboratory along with Dr. G R Karpagam at PSG College of Technology. He is a Life Member of the Institution of Engineers- India (IEI), International Association of Engineers (IAENG) and Indian Society of Systems for Science and Engineering (ISSE). He has published papers in peer reviewed National/International Journals and Conferences and a Reviewer of International Journals. 

Dr. G. R. Karpagam is a professor with 20 years of experience in Computer Science and Engineering at PSG College of Technology. Holding a B.E., M.E., and Ph.D. in Computer Science and Engineering, her areas of specialization include database management systems, data structures and algorithms, service-oriented architectures, cloud computing, model-driven architectures and security. She is a member of many academic and professional associations, e.g. the IEEE, ACM, ISTE, IE Institution of Engineers, and ACCS. 

Inhalt
An Evolutionary Computing Approach to Solve Object Identification Problem for fall detection in Computer Vision based Video Surveillance Applications.- Texture-dependent Optimal Fractional-order Framework for Image Quality Enhancement through Memetic Inclusions in Cuckoo Search and Sine-Cosine Algorithms.- Artificial Bee Colony: Theory, Literature Review, and Application in Image Segmentation.- Applications of Memetic Algorithms in Image Processing Using Deep Learning.- Recent Applications of Swarm-based Algorithms to Color Quantization.- Hybrid Biogeography Based Optimization Techniques for Geo-Spatial Feature Extraction: A Brief Survey.- An Efficient Copy-move Forgery Detection Technique using Nature-Inspired Optimization Algorithm.- Design and Implementation of Hybrid Plate Tectonics Neighborhood based ADAM's Optimization and its application on Crop Recommendation.- An Evolutionary Memetic Weighted Associative Classification Algorithm for Heart Disease Prediction.