000			02741 a2200229 4500
020			_a9781119488750
040			_cIIT Kanpur
041			_aeng
082			_a006.42015181 _bD53q
100			_aDey, Sandip
245			_aQuantum inspired meta-heuristics for image analysis _cSandip Dey, Siddhartha Bhattacharyya, and Ujjwal Maulik
260			_bJohn Wiley _c2019 _aNew Jersey
300			_axvi, 358p
520			_aIntroduces quantum inspired techniques for image analysis for pure and true gray scale/color images in a single/multi-objective environment This book will entice readers to design efficient meta-heuristics for image analysis in the quantum domain. It introduces them to the essence of quantum computing paradigm, its features, and properties, and elaborates on the fundamentals of different meta-heuristics and their application to image analysis. As a result, it will pave the way for designing and developing quantum computing inspired meta-heuristics to be applied to image analysis. Quantum Inspired Meta-heuristics for Image Analysis begins with a brief summary on image segmentation, quantum computing, and optimization. It also highlights a few relevant applications of the quantum based computing algorithms, meta-heuristics approach, and several thresholding algorithms in vogue. Next, it discusses a review of image analysis before moving on to an overview of six popular meta-heuristics and their algorithms and pseudo-codes. Subsequent chapters look at quantum inspired meta-heuristics for bi-level and gray scale multi-level image thresholding; quantum behaved meta-heuristics for true color multi-level image thresholding; and quantum inspired multi-objective algorithms for gray scale multi-level image thresholding. Each chapter concludes with a summary and sample questions. Provides in-depth analysis of quantum mechanical principles Offers comprehensive review of image analysis Analyzes different state-of-the-art image thresholding approaches Detailed current, popular standard meta-heuristics in use today Guides readers step by step in the build-up of quantum inspired meta-heuristics Includes a plethora of real life case studies and applications Features statistical test analysis of the performances of the quantum inspired meta-heuristics vis-à-vis their conventional counterparts Quantum Inspired Meta-heuristics for Image Analysis is an excellent source of information for anyone working with or learning quantum inspired meta-heuristics for image analysis.
650			_aHeuristic algorithms
650			_aMetaheuristics
650			_aImage analysis
650			_aImage segmentation
700			_aBhattacharyya, Siddhartha
700			_aMaulik, Ujjwal
942			_cBK
999			_c560917 _d560917