Applications
In terms of applications, the use of corner detection and blob detection are also overlapping. Today, a main application of interest points is to signal points/regions in the image domain that are likely candidates to be useful for image matching and view-based object recognition. For this purpose, several types of corner detectors and blob detectors have been demonstrated to be highly useful in practical applications (see respective articles for references). Blob detectors and corner detectors have also been used as primitives for texture recognition, texture analysis and for constructing object models from multiple views of textured objects.
If one aims at drawing a distinction between corner detectors and blob detectors, this can often be done in terms of their localization properties at corner structures. For a junction structure in the image domain that corresponds to an intersection of physical edges in the three-dimensional world, the localization properties of a corner detector will in most cases be much better than the localization properties that would be obtained from a blob detector. Hence, for the purpose of computing structure and motion from multiple views, corner detectors will in many cases have advantages compared to blob detectors in terms of smaller localization error. Notwithstanding this, blob descriptors have also been demonstrated to be useful when relating object models to temporal imagery.
In terms of concepts, there is also a close relationship between the notion of interest points and ridge detectors, which are often used to signal the presence of elongated objects. Moreover, with regard to features that extend along one-dimensional curves in image space, there is the related notion of edge detectors which satisfy similar requirements in terms of operational definitions, well-defined extent, locally high information contents and repeatability.
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