Feature Detection (computer vision)
von Betascript Publishing
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Beschreibung
High Quality Content by WIKIPEDIA articles! In computer vision and image processing the concept of feature detection refers to methods that aim at computing abstractions of image information and making local decisions at every image point whether there is an image feature of a given type at that point or not. The resulting features will be subsets of the image domain, often in the form of isolated points, continuous curves or connected regions.There is no universal or exact definition of what constitutes a feature, and the exact definition often depends on the problem or the type of application. Given that, a feature is defined as an "interesting" part of an image, and features are used as a starting point for many computer vision algorithms. Since features are used as the starting point and main primitives for subsequent algorithms, the overall algorithm will often only be as good as its feature detector. Consequently, the desirable property for a feature detector is repeatability: whether or not the same feature will be detected in two or more different images of the same scene.
Weitere Informationen
Sprache:
Englisch
Seitenanzahl:
96
Herausgeber:
Surhone, Lambert M.
Tennoe, Mariam T.
Henssonow, Susan F.
Medientyp:
Taschenbuch
Verlag:
Betascript Publishing
Stammdaten
Produkttyp:
Taschenbuch
Verpackungsabmessungen:
0.229 x 0.152 x 0.006 m; 0.15 kg
GTIN:
09786131388415
DUIN:
VU3K57HSVFK
CHF 27.50