Abstract
We present in this paper a new approach to modeling an image in a pattern recognition context. It relates to a generalization of the planar Markov modeling, which we shall call Planar Multi-Classifier Modeling (PMCM). These models allow exploring various classifier types, among others, Markov ones, to model delimited bands of an image associated with a given pattern. Determining the different parameters of the proposed planar model is made explicit. Various PMCM architectures are proposed; in this paper we present the PMCM-NN/SVM architecture. The validation has been performed in a security context based on off-line handwritten signature verification. The different experiments, carried out on two public databases: the SID-Signature database and the GPDS-160 Signature database, have led to promising results.
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Abdelghani, I.A.B., Amara, N.E.B. (2015). Planar Multi-classifier Modelling-NN/SVM: Application to Off-line Handwritten Signature Verification. In: Herrero, Á., Baruque, B., Sedano, J., Quintián, H., Corchado, E. (eds) International Joint Conference. CISIS 2015. Advances in Intelligent Systems and Computing, vol 369. Springer, Cham. https://doi.org/10.1007/978-3-319-19713-5_8
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DOI: https://doi.org/10.1007/978-3-319-19713-5_8
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