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A Theory of Shape Identification [[electronic resource] /] / by Frédéric Cao, José-Luis Lisani, Jean-Michel Morel, Pablo Musé, Frédéric Sur



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Autore: Cao Frédéric Visualizza persona
Titolo: A Theory of Shape Identification [[electronic resource] /] / by Frédéric Cao, José-Luis Lisani, Jean-Michel Morel, Pablo Musé, Frédéric Sur Visualizza cluster
Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008
Edizione: 1st ed. 2008.
Descrizione fisica: 1 online resource (XII, 264 p. 171 illus., 12 illus. in color.)
Disciplina: 595.789
Soggetto topico: Geometry
Mathematics
Visualization
Optical data processing
Artificial intelligence
Game theory
Image Processing and Computer Vision
Artificial Intelligence
Computer Imaging, Vision, Pattern Recognition and Graphics
Game Theory, Economics, Social and Behav. Sciences
Persona (resp. second.): LisaniJosé-Luis
MorelJean-Michel
MuséPablo
SurFrédéric
Note generali: Bibliographic Level Mode of Issuance: Monograph
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: 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.
Sommario/riassunto: 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.
Titolo autorizzato: Theory of Shape identification  Visualizza cluster
ISBN: 3-540-68481-6
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 996466380403316
Lo trovi qui: Univ. di Salerno
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Serie: Lecture Notes in Mathematics, . 0075-8434 ; ; 1948