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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 its response properties to different types of image structures at different scales, the LoG [[blob detection|blob detector]] is also mentioned in the article on [[corner detection]].
=== [[Ridge_detection|Ridges]] ===
For elongated objects, the notion of ''ridges'' is a natural tool. A ridge descriptor computed from a grey-level image can be seen as a generalization of the a medial axis. From a practical viewpoint, a ridge can be thought of as a one-dimensional curve that represents an axis of symmetry, and in addition has an attribute of local ridge width associated with each each ridge point. Unfortunately, however, it is algorithmically harder to extract ridge features from general classes of grey-level images than edge-, corner- or blob features. Nevertheless, ridge descriptors are frequently used for road extraction in aerial images and for extracting blood vessels in medical images -- see [[ridge detection]].
== Feature detectors ==
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