In recent years bio-inspired computational theories and tools have developed to assist people in extracting knowledge from high dimensional data. These differ in how they take a more evolutionary approach to learning, as opposed to traditional artificial intelligence (AI) and what could be described as 'creationist' methods. Instead bio-inspired computing takes a bottom-up, de-centralized approach that often involves the method of specifying a set of simple rules, a set of simple organisms which adhere to those rules, and of iteratively applying those rules.
Bio-Inspired Computing for Image and Video Processing covers interesting and challenging new theories in image and video processing. It addresses the growing demand for image and video processing in diverse application areas, such as secured biomedical imaging, biometrics, remote sensing, texture understanding, pattern recognition, content-based image retrieval, and more.
This book is perfect for students following this topic at both undergraduate and postgraduate level. It will also prove indispensable to researchers who have an interest in image processing using bio-inspired computing.
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About the Author
D. P. Acharjya received his Ph.D. in Computer Science from Berhampur University, India; M. Tech. degree in Computer Science from Utkal University, India; and M. Sc. from NIT, Rourkela, India. Currently he is working as a Professor in the School of Computer Science and Engineering, VIT University, Vellore, India. He has authored more than 60 national and international journal and conference papers to his credit. He has also written four text books and edited six books to his credit. He has been awarded with Gold Medal in M. Sc; Eminent Academician Award from Khallikote Sanskrutika Parisad, Brahmapur, Odisha; Outstanding Educator and Scholar Award from NFED, Coimbatore, India; and The Best Citizens of India Award from The International Publishing House, New Delhi, India. He is acting as an editorial board member of various journals and reviewer of IEEE Fuzzy Sets and Systems, Applied Soft Computing, and Knowledge base Systems. He is associated with many professional bodies ACM, CSI, ISTE, IMS, AMTI, ISIAM, OITS, IACSIT, CSTA, and IAENG. He was founder secretary of OITS Rourkela chapter. His current research interests include rough computing, knowledge representation, bio-inspired computing, data mining, granular computing and business intelligence.
V. Santhi received her Ph.D. in CSE from VIT University; M. Tech. in CSE from Pondicherry University; and B. Tech. in CSE from Bharathidasan University, India. She is currently working as Associate Professor in School of Computer Science and Engineering, VIT University. She has 18 years of experience in academic and 3 years of experience in Industry. She had served as Head of Department for more than eight years in engineering colleges. She has received research award for publishing research papers in refereed Journals from VIT University 3 times consecutively. She has guided more than 80 graduate projects and more than 50 post graduate level projects. Her publications are indexed in IEEE Computer Society, SPIE Digital Library, NASA Astrophysics Data Systems, SCOPUS and ACM Digital Library. She is a reviewer of IEEE Transaction on Multimedia Security, IEEE Transaction on Image Processing, IET–Image Processing, International Journal of Information and Computer Security. She is member of IEEE Signal Processing Society, CSI and IACSIT. She has published many papers in refereed Journals and in International Conferences. She has contributed many chapters and currently in the process of editing books. Her current research include digital image processing, digital signal processing, multimedia security, soft computing, bio-Inspired computing, and remote sensing.
Table of Contents
Part I: Bio-inspired Computing Models and Algorithms
Chapter 1: Genetic Algorithm and BFOA based Iris and Palmprint Multimodal Biometric Digital Watermarking Models
Chapter 2: Multilevel Thresholding for Image Segmentation using Cricket Chirping Algorithm
Chapter 3: Algorithms for Drawing Graphics Primitives on Honey-Comb Model Inspired Grid
Chapter 4: Electrical Impedance Tomography Using Evolutionary Computing: A Review
Part II: Bio-inspired OptimizationTechniques
Chapter 5: An Optimized False Positive Free Video Watermarking System in Dual Transform Domain
Chapter 6: Bone Tissue Segmentation using Spiral Optimization and Gaussian Thresholding
Chapter 7: Digital Image Segmentation using Computational Intelligence Approaches
Chapter 8: Digital Color Image Watermarking using DWT SVD Cuckoo Search Optimization
Chapter 9: Digital Image Watermarking Scheme in Transform Domain using Particle Swarm Optimization Technique
Part III: Bio-inspired Computing Applications to Image and Video Processing
Chapter 10: Evolutionary Algorithms for the Efficient Design of Multiplier-less Image Filter
Chapter 11: Fusion of Texture and Shape based Statistical Features for MRI Image Retrieval System
Chapter 12: Singular Value Decomposition - Principal Component Analysis based Object Recognition Approach
Chapter 13: The kd-ORS Tree: An Efficient Indexing Technique for Content Based Image Retrieval
Chapter 14: An Efficient Image Compression Algorithm based on the Integration of Histogram Indexed Dictionary and the Huffman Encoding for Medical Images