- Tytuł:
- Signature recognition with a hybrid approach combining modular neural networks and fuzzy logic for response integration
- Autorzy:
-
Beltrán, M.
Melin, P.
Trujillo, L.
Lopez, M. - Powiązania:
- https://bibliotekanauki.pl/articles/384541.pdf
- Data publikacji:
- 2010
- Wydawca:
- Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
- Tematy:
-
pattern recognition
neural networks
fuzzy logic - Opis:
- This paper describes a modular neural network (MNN) with fuzzy integration 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 and a fuzzy inference system. The experimental results obtained using a database of 30 individual’s shows that the modular architecture can achieve a very high 99.33% 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. Furthermore we consider the verification of signatures as false acceptance, false rejection and error recognition of the MNN.
- Źródło:
-
Journal of Automation Mobile Robotics and Intelligent Systems; 2010, 4, 1; 20-27
1897-8649
2080-2145 - Pojawia się w:
- Journal of Automation Mobile Robotics and Intelligent Systems
- Dostawca treści:
- Biblioteka Nauki
Artykuł