Flexible Neural Network Architecture for Handwritten Signatures Recognition

• Autorzy: Połap D. , Woźniak M.

Identyfikatory

DOI

10.1515/eletel-2016-0027

• Języki publikacji: EN

Abstrakty

EN

This article illustrates modeling of flexible neural networks for handwritten signatures preprocessing. An input signature is interpolated to adjust inclination angle, than descriptor vector is composed. This information is preprocessed in proposed flexible neural network architecture, in which some neurons are becoming crucial for recognition and adapt to classification purposes. Experimental research results are compared in benchmark tests with classic approach to discuss efficiency of proposed solution.

Słowa kluczowe

EN

neural networks; handwritten signatures preprocessing; signature recognition; chebyshev polynomials

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2016
• Tom: Vol. 62, No. 2
• Strony: 197--202
• Opis fizyczny: Bibliogr. 26 poz., rys., wykr.

Twórcy

autor

Połap D.

• Institute of Mathematics, Silesian University of Technology, Kaszubska 23, 44-100 Gliwice, Poland

autor

Woźniak M.

• Institute of Mathematics, Silesian University of Technology, Kaszubska 23, 44-100 Gliwice, Poland

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.