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- Blob_detection abstract "In the field of computer vision, blob detection refers to mathematical methods that are aimed at detecting regions in a digital image that differ in properties, such as brightness or color, compared to areas surrounding those regions. Informally, a blob is a region of a digital image in which some properties are constant or vary within a prescribed range of values; all the points in a blob can be considered in some sense to be similar to each other.Given some property of interest expressed as a function of position on the digital image, there are two main classes of blob detectors: (i) differential methods, which are based on derivatives of the function with respect to position, and (ii) methods based on local extrema, which are based on finding the local maxima and minima of the function. With the more recent terminology used in the field, these detectors can also be referred to as interest point operators, or alternatively interest region operators (see also interest point detection and corner detection).There are several motivations for studying and developing blob detectors. One main reason is to provide complementary information about regions, which is not obtained from edge detectors or corner detectors. In early work in the area, blob detection was used to obtain regions of interest for further processing. These regions could signal the presence of objects or parts of objects in the image domain with application to object recognition and/or object tracking. In other domains, such as histogram analysis, blob descriptors can also be used for peak detection with application to segmentation. Another common use of blob descriptors is as main primitives for texture analysis and texture recognition. In more recent work, blob descriptors have found increasingly popular use as interest points for wide baseline stereo matching and to signal the presence of informative image features for appearance-based object recognition based on local image statistics. There is also the related notion of ridge detection to signal the presence of elongated objects.".
- Blob_detection wikiPageExternalLink lowe04distinctive.html.
- Blob_detection wikiPageExternalLink matas-bmvc02.pdf.
- Blob_detection wikiPageExternalLink opensurf.html.
- Blob_detection wikiPageExternalLink cvap198.html.
- Blob_detection wikiPageExternalLink cvap201.html.
- Blob_detection wikiPageExternalLink LG94-ECCV.html.
- Blob_detection wikiPageExternalLink Lin08-EncCompSci.html.
- Blob_detection wikiPageExternalLink Lin92-IJCV.html.
- Blob_detection wikiPageExternalLink book.html.
- Blob_detection wikiPageExternalLink mikolajczyk_ijcv2004.pdf.
- Blob_detection wikiPageExternalLink papers.html.
- Blob_detection wikiPageID "6840205".
- Blob_detection wikiPageRevisionID "600013652".
- Blob_detection hasPhotoCollection Blob_detection.
- Blob_detection subject Category:Feature_detection.
- Blob_detection comment "In the field of computer vision, blob detection refers to mathematical methods that are aimed at detecting regions in a digital image that differ in properties, such as brightness or color, compared to areas surrounding those regions.".
- Blob_detection label "Blob detection".
- Blob_detection label "Reconocimiento de regiones".
- Blob_detection label "Riconoscimento di regioni".
- Blob_detection sameAs Reconocimiento_de_regiones.
- Blob_detection sameAs Riconoscimento_di_regioni.
- Blob_detection sameAs m.0gs011.
- Blob_detection sameAs Q1026711.
- Blob_detection sameAs Q1026711.
- Blob_detection wasDerivedFrom Blob_detection?oldid=600013652.
- Blob_detection isPrimaryTopicOf Blob_detection.