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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Modular Neural Networks with Fuzzy Response Integration for Signature Recognition
verfasst von : Mónica Beltrán, Patricia Melin, Leonardo Trujillo
Erschienen in: Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition
Verlag: Springer Berlin Heidelberg
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This chapter describes a modular neural network (MNN) for the problem of signature recognition. Currently, biometric identification has gained a great deal of research interest within the pattern recognition community. For instance, many attempts have been made in order to automate the process of identifying a person’s handwritten signature, however this problem has proven to be a very difficult task. In this work, we propose a MNN that has three separate modules, each using different image features as input, these are: edges, wavelet coefficients, and the Hough transform matrix. Then, the outputs from each of these modules are combined using a Sugeno fuzzy integral. The experimental results obtained using a database of 30 individual’s shows that the modular architecture can achieve a very high 98% recognition accuracy with a test set of 150 images. Therefore, we conclude that the proposed architecture provides a suitable platform to build a signature recognition system.