Abstract
It is argued that traditional pattern recognition methods are inadequate for the tasks confronting computer vision. In an effort to overcome their limitations, a new approach has been developed, in which the concept of pattern is replaced by the group-theoretical notions of representations and invariants. By applying these ideas to the symbolic representation of images, it is possible to derive some very general constraints on the effectiveness of symbolic descriptions from the structure of the image vector space and the transformations which act upon it. The theory is illustrated with some simple examples and then applied to a number of practical problems, including feature description, texture analysis and segmentation. The paper is concluded with a discussion of some generalisations and extensions.
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Wilson, R. (1988). Is vision a pattern recognition problem?. In: Kittler, J. (eds) Pattern Recognition. PAR 1988. Lecture Notes in Computer Science, vol 301. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-19036-8_1
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DOI: https://doi.org/10.1007/3-540-19036-8_1
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