In this paper, we present the problem of noisy images recognition and in particular the stage of primitives selection in a classification process. We suppose that segmentation and statistical features extraction on documentary images are realized. We describe precisely the use of concept lattice and compare it with a decision tree in a recognition process. From the experimental results, it appears that concept lattice is more adapted to the context of noisy images. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Guillas, S., Bertet, K., & Ogier, J. M. (2006). A generic description of the concept lattices’ classifier: Application to symbol recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3926 LNCS, pp. 47–60). Springer Verlag. https://doi.org/10.1007/11767978_5
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