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＜電子ブック＞
A Theory of Shape Identification / by Frédéric Cao, José-Luis Lisani, Jean-Michel Morel, Pablo Musé, Frédéric Sur
(Lecture Notes in Mathematics. ISSN:16179692 ; 1948)

版	1st ed. 2008.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	2008
本文言語	英語
大きさ	XII, 264 p. 171 illus., 12 illus. in color : online resource
著者標目	*Cao, Frédéric author Lisani, José-Luis author Morel, Jean-Michel author Musé, Pablo author Sur, Frédéric author SpringerLink (Online service)
件　名	LCSH:Geometry LCSH:Information visualization LCSH:Computer vision LCSH:Artificial intelligence LCSH:Image processing -- Digital techniques  全ての件名で検索 LCSH:Game theory FREE:Geometry FREE:Data and Information Visualization FREE:Computer Vision FREE:Artificial Intelligence FREE:Computer Imaging, Vision, Pattern Recognition and Graphics FREE:Game Theory
一般注記	Extracting Image boundaries -- Extracting Meaningful Curves from Images -- Level Line Invariant Descriptors -- Robust Shape Directions -- Invariant Level Line Encoding -- Recognizing Level Lines -- A Contrario Decision: the LLD Method -- Meaningful Matches: Experiments on LLD and MSER -- Grouping Shape Elements -- Hierarchical Clustering and Validity Assessment -- Grouping Spatially Coherent Meaningful Matches -- Experimental Results -- The SIFT Method -- The SIFT Method -- Securing SIFT with A Contrario Techniques Recent years have seen dramatic progress in shape recognition algorithms applied to ever-growing image databases. They have been applied to image stitching, stereo vision, image mosaics, solid object recognition and video or web image retrieval. More fundamentally, the ability of humans and animals to detect and recognize shapes is one of the enigmas of perception. The book describes a complete method that starts from a query image and an image database and yields a list of the images in the database containing shapes present in the query image. A false alarm number is associated to each detection. Many experiments will show that familiar simple shapes or images can reliably be identified with false alarm numbers ranging from 10-5 to less than 10-300. Technically speaking, there are two main issues. The first is extracting invariant shape descriptors from digital images. The second is deciding whether two shape descriptors are identifiable as the same shape or not. A perceptual principle, the Helmholtz principle, is the cornerstone of this decision. These decisions rely on elementary stochastic geometry and compute a false alarm number. The lower this number, the more secure the identification. The description of the processes, the many experiments on digital images and the simple proofs of mathematical correctness are interlaced so as to make a reading accessible to various audiences, such as students, engineers, and researchers HTTP:URL=https://doi.org/10.1007/978-3-540-68481-7

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