Image Feature Detectors and Descriptors
Foundations and Applications
Published on 25. April 2018
Book
Paperback/Softback
IX, 438 pages
978-3-319-80441-5 (ISBN)
Description
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.
More details
Series
Edition
Softcover reprint of the original 1st ed. 2016
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
84 farbige Abbildungen, 129 s/w Abbildungen
IX, 438 p. 213 illus., 84 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 25 mm
Weight
674 gr
ISBN-13
978-3-319-80441-5 (9783319804415)
DOI
10.1007/978-3-319-28854-3
Schweitzer Classification
Other editions
Additional editions
Ali Ismail Awad | Mahmoud Hassaballah
Image Feature Detectors and Descriptors
Foundations and Applications
Book
03/2016
Springer
€106.99
Shipment within 10-15 days
Content
Introduction.- 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.- Satellite Image Registration: A Comparative Study Using Invariant Local Features.- Redundancy Elimination in Video Summarization.- A Real Time Dactylology Based Selective Image Encryption Using Speeded Up Robust Features Extraction Technique 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.