Feature detection (computer vision): Difference between revisions

Revision as of 08:07, 9 August 2007

Revision as of 08:08, 9 August 2007

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{{Unreferenced|article|date=August 2007}}

In [[computer vision]] and [[image processing]] the concept of '''feature detection''' refers to methods that aim at computing abstractions of image information and making local decisions at every image point whether there is an [[image feature]] of a given type at that point or not. The resulting features will be subsets of the image ___domain, often in the form of isolated points, continuous curves or connected regions.

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== References ==

Please, see the respective articles on [[edge detection]], [[corner detection]], [[blob detection]] and [[ridge detection]] for main references within each feature category.

*Canny, J., A Computational Approach To Edge Detection, IEEE Trans. Pattern Analysis and Machine Intelligence, 8:679-714, 1986.

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* {{cite conference

| author=C. Harris and M. Stephens

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| url=http://citeseer.ist.psu.edu/654168.html

}}

* {{cite conference

| author=J. Matas, O. Chum, M. Urban and T. Pajdla

| title=Robust wide baseline stereo from maximally stable extremum regions