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  • 1
    UID:
    almahu_9947363900102882
    Format: XII, 264 p. 171 illus., 12 illus. in color. , online resource.
    ISBN: 9783540684817
    Series Statement: Lecture Notes in Mathematics, 1948
    Content: 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.
    Note: 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.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783540684800
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    gbv_1647374383
    Format: Online-Ressource (digital)
    ISBN: 9783540684817
    Series Statement: SpringerLink
    Content: 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.
    Content: 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.
    Note: Includes bibliographical references and index
    Additional Edition: ISBN 9783540684800
    Additional Edition: Buchausg. u.d.T. Cao, Frédéric A theory of shape identification Berlin : Springer, 2008 ISBN 9783540684800
    Language: English
    Subjects: Mathematics
    RVK:
    Keywords: Formbeschreibung ; Bilderkennung ; Automatische Identifikation ; Maschinelles Sehen ; Mustererkennung
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
    Author information: Morel, Jean-Michel 1953-
    Library Location Call Number Volume/Issue/Year Availability
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