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Awad A.I., Hassaballah M. (eds.) Image Feature Detectors and Descriptors. Foundations and Applications

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Awad A.I., Hassaballah M. (eds.) Image Feature Detectors and Descriptors. Foundations and Applications
Springer, 2016. — 438 p.: 213 illus. — ISBN 978-3-319-28852-9.
This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition.
Detection and Description of Image Features: An Introduction
Part I Foundations of Image Feature Detectors and Descriptors
Image Features Detection, Description and Matching
A Review of Image Interest Point Detectors: From Algorithms to FPGA Hardware Implementations
Image Features Extraction, Selection and Fusion for Computer Vision
Image Feature Extraction Acceleration
Part II Applications of Image Feature Detectors and Descriptors
Satellite Image Matching and Registration: A Comparative Study Using Invariant Local Features
Redundancy Elimination in Video Summarization
A Real Time Dactylology Based Feature Extraction for Selective Image Encryption and Artificial Neural Network
Spectral Reflectance Images and Applications
Image Segmentation Using an Evolutionary Method Based on Allostatic Mechanisms
Image Analysis and Coding Based on Ordinal Data Representation
Intelligent Detection of Foveal Zone from Colored Fundus Images of Human Retina Through a Robust Combination of Fuzzy-Logic and Active Contour Model
Registration of Digital Terrain Images Using Nondegenerate Singular Points
Visual Speech Recognition with Selected Boundary Descriptors
Application of Texture Features for Classification of Primary Benign and Primary Malignant Focal Liver Lesions
Application of Statistical Texture Features for Breast Tissue Density Classification
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