Abstract
Data-based features in images such as key point locations or potential parts of object boundaries can be extracted from local image characteristics. Boundary parts are generated from the results of an edge enhancement step while key point locations are local extrema of some local object property. Features may also be computed from samples of an object’s boundary or interior.
Potential object boundary parts are used for detecting or delineating objects in images. Key points may, in some simple cases, also be used to detect objects. In most cases, however, object characteristics are too complex to be captured by the attributes of a key point. They can be important attributes nonetheless. Key points define an object-dependent reference system in which they may be used to map objects of the same class onto each other.
Concepts, notions and definitions introduced in this chapter
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This can be difficult, however, since texture measures are estimated from a local neighborhood that is assumed to have the same texture. This is not true at texture boundaries.
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Toennies, K.D. (2012). Feature Detection. In: Guide to Medical Image Analysis. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-2751-2_5
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