Abstract
We apply the dynamic link matching algorithm to object recognition in gray level images. The algorithm is able to map from one view of an object to different-e. g., translated, rotated, or mirror-reflected—views, being at the same time tolerant of small distortions. A sparse representation (10%) of the image data is used as a boundary condition for a self-organizing mechanism which performs the object match within a modest number of iterations (~102). The mechanism can be derived from local neural dynamics [1].
Supported by a grant from the German Federal Ministry for Science and Technology (413-5839-01 IN 101 B/9).
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© 1993 Springer-Verlag London Limited
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Konen, W., Vorbrüggen, J.C. (1993). Applying Dynamic Link Matching to Object Recognition in Real World Images. In: Gielen, S., Kappen, B. (eds) ICANN ’93. ICANN 1993. Springer, London. https://doi.org/10.1007/978-1-4471-2063-6_288
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DOI: https://doi.org/10.1007/978-1-4471-2063-6_288
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