Abstract
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.
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References
Ballard, D.: Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13(2), 111–122 (1981)
Zhang, D.: Automated Biometrics Technologies and Systems, Hong Kong Polytechnic University, ch. 10, pp. 203–206. Kluwer Academic Publishers, Dordrecht (2000)
Keller, J., Gader, P., Hocaoglu, A.: Integrals in image processing and recognition. In: Grabisch, M., et al. (eds.) Fuzzy Measures and Integrals: Theory and Applications, pp. 435–466. Physica-Verlag, NY (2000)
Grabisch, M.: A new algorithm for identifying fuzzy measures and its application to pattern recognition. In: Proc. of 4th IEEE Int. Conf. on Fuzzy Systems, Yokohama, Japan, pp. 145–150 (1995)
Grabisch, M., Murofushi, T., Sugeno, M.: Fuzzy Measures and Integrals: Theory and Applications, pp. 348–373. Physica-Verlag, NY (2000)
Castillo, O., Melin, P., Kacprzyk, J., Pedrycz, W.: Hybrid Intelligent Systems Analysis and Design. Springer, Heidelberg (2007)
Mendoza, O., Melin, P.: The Fuzzy Sugeno Integral as a Decision Operator in the Recognition of Images with Modular Neural Networks, Tijuana Institute of Technology, México. Springer, Heidelberg (2007)
Melin, P., Mancilla, A., González, C., Bravo, D.: Modular Neuronal Networks with Fuzzy Sugeno Integral Response Integration for Face and Fingerprint Recognition. In: The International MultiConference in Computer Science and Computer Enginnering, Las Vegas, USA, vol.1, pp. 91–97 (2004)
Melin, P., Mancilla, A., Lopez, M., Solano, D., Soto, M., Castillo, O.: Pattern Recognition for Industrial Security using the Fuzzy Sugeno Integral and Modular Neural Network. In: Soft Computing in Industrial Applications, vol. 39, pp. 4–9. Springer, Heidelberg (2007)
Melin, P., Felix, C., Castillo, O.: Face Recognition using Modular Neural Networks and the Fuzzy Sugeno Integral for Response Integration. Journal of Intelligent Systems 20(2), 275–29 (2005)
Melin, P., Gonzalez, C., Bravo, D., Gonzalez, F., Martinez, G.: Modular Neural Networks and Fuzzy Sugeno Integral for Pattern Recognition: Then Case of Human Face and Fingerprint, Tijuana Institute of Technology, Tijuana, Mexico. Springer, Heidelberg (2007)
Melin, P., Castillo, O.: Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems, 1st edn. Studies in Fuzziness and Soft Computing. Springer, Heidelberg (2005)
Melin, P., Castillo, O.: Hybrid Intelligent Systems for Pattern Recognition. Springer, Heidelberg (2005)
Kung, S., Mak, M., Lin, S.: Biometric Authentication A Machine Learning Approach. Prentice Hall Information and System Sciences Series (Kailath, T., Series ed.), pp. 27–49 (2005)
Santoso, S., Powers, E., Grady, E.: Power quality disturbance data compression using wavelet transform methods. IEEE Trans. On Power Delivery 12(3), 1250–1257 (1997)
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Beltrán, M., Melin, P., Trujillo, L. (2009). Modular Neural Networks with Fuzzy Response Integration for Signature Recognition. In: Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition. Studies in Computational Intelligence, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04516-5_5
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DOI: https://doi.org/10.1007/978-3-642-04516-5_5
Publisher Name: Springer, Berlin, Heidelberg
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