| dbo:abstract |
Die Census-Transformation (CT) (engl. Census Transform) wurde von Zabih und Woodfill vorgeschlagen und berechnet für jeden quadratischen Pixelbereich eines Bildes einen Bit-String als Signatur. Dadurch können insbesondere über die Hamming-Distanz der Bit-Strings schnell übereinstimmende Bereiche der Bilder ermittelt werden – beispielsweise zur Erzeugung einer disparity map als Vorstufe zur Bestimmung des optischen Flusses (optical flow) oder einer Stereo Disparität (stereo matching) von zeitlich folgenden bzw. gleichzeitig aufgenommenen Bildern. (de) The census transform (CT) is an image operator that associates to each pixel of a grayscale image a binary string, encoding whether the pixel has smaller intensity than each of its neighbours, one for each bit. It is a non-parametric transform that depends only on relative ordering of intensities, and not on the actual values of intensity, making it invariant with respect to monotonic variations of illumination, and it behaves well in presence of multimodal distributions of intensity, e.g. along object boundaries. It has applications in computer vision, and it is commonly used in visual correspondence problems such as optical flow calculation and disparity estimation. The census transform is related to the rank transform, that associates to each pixel the number of neighbouring pixels with higher intensity than the pixel itself, and was introduced in the same paper. (en) |
| dbo:thumbnail |
wiki-commons:Special:FilePath/Glasses_800_edit.png?width=300 |
| dbo:wikiPageExternalLink |
https://www.mia.uni-saarland.de/Publications/hafner-ssvm13.pdf https://www.researchgate.net/publication/221113496 http://www.cs.duke.edu/courses/spring06/cps296.1/handouts/Zabih%20Woodfill%201994.pdf |
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dbr:Monotonic_function dbr:Grayscale dbr:Correspondence_problem dbr:Computer_vision dbr:Byte dbr:Local_binary_patterns dbr:Optical_flow dbr:Hamming_distance dbc:Feature_detection_(computer_vision) dbr:Binocular_disparity dbr:Pixel dbr:Illumination_(image) |
| dbp:align |
right (en) |
| dbp:alt |
Grayscale conversion followed by census transform (en) Image of glasses and bottles (en) |
| dbp:caption |
A synthetic scene (en) Grayscale conversion followed by census transform (en) |
| dbp:direction |
vertical (en) |
| dbp:header |
Example of census transform (en) |
| dbp:image |
Census transform example.png (en) Glasses_800_edit.png (en) |
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300 (xsd:integer) |
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dbt:Cite_conference dbt:Multiple_image |
| dct:subject |
dbc:Feature_detection_(computer_vision) |
| rdfs:comment |
Die Census-Transformation (CT) (engl. Census Transform) wurde von Zabih und Woodfill vorgeschlagen und berechnet für jeden quadratischen Pixelbereich eines Bildes einen Bit-String als Signatur. Dadurch können insbesondere über die Hamming-Distanz der Bit-Strings schnell übereinstimmende Bereiche der Bilder ermittelt werden – beispielsweise zur Erzeugung einer disparity map als Vorstufe zur Bestimmung des optischen Flusses (optical flow) oder einer Stereo Disparität (stereo matching) von zeitlich folgenden bzw. gleichzeitig aufgenommenen Bildern. (de) The census transform (CT) is an image operator that associates to each pixel of a grayscale image a binary string, encoding whether the pixel has smaller intensity than each of its neighbours, one for each bit. It is a non-parametric transform that depends only on relative ordering of intensities, and not on the actual values of intensity, making it invariant with respect to monotonic variations of illumination, and it behaves well in presence of multimodal distributions of intensity, e.g. along object boundaries. It has applications in computer vision, and it is commonly used in visual correspondence problems such as optical flow calculation and disparity estimation. (en) |
| rdfs:label |
Census-Transformation (de) Census transform (en) |
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wikidata:Census transform dbpedia-de:Census transform https://global.dbpedia.org/id/8rLY |
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wikipedia-en:Census_transform?oldid=1051970804&ns=0 |
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wiki-commons:Special:FilePath/Glasses_800_edit.png wiki-commons:Special:FilePath/Census_transform_example.png |
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wikipedia-en:Census_transform |
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dbr:Rank_transform |
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dbr:Local_binary_patterns dbr:Rank_transform dbr:Semi-global_matching |
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wikipedia-en:Census_transform |
