Feature detection (computer vision): Difference between revisions

Revision as of 14:37, 22 September 2006

Revision as of 14:38, 22 September 2006

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Blobs provide a complementary description of image structures in terms of regions, as opposed to corners that are more point-like. Nevertheless, blob descriptors often contain a preferred point (a local maximum of an operator response or a center of gravity) which means that many blob detectors may also be regarded as interest point operators. Blob detectors can detect areas in an image which are too smooth to be detected by a corner detector.

Consider shrinking an image and then performing corner detection. The detector will respond to points which are sharp in the shrunk image, but may be smooth in the original image. It is at this point that the difference between a corner detector and a blob detector becomes somewhat vague. To a large extent, this distinction can be remedied by including an appropriate notion of scale. Nevertheless, due to itstheir response properties to different types of image structures at different scales, the LoG and DoH [[blob detection|blob detectors]] are also mentioned in the article on [[corner detection]].

=== [[Ridge_detection|Ridges]] ===