Fuzzy Logic Based Adaptive Resonance Theory-1 Approach for Offline Signature Verification

• Autorzy: Jain C. , Singh P. , Rana A.

Identyfikatory

DOI

10.1515/ipc-2017-0015

• Języki publikacji: EN

Abstrakty

EN

This paper presents the use fuzzy logic with adaptive resonance theory-1 in signature verification. Fuzzy model is capable of stable learning of recognition categories in response to arbitrary sequences of binary input pattern. The work was carried out on two famous available signature corpuses i.e. MCYT (Online Spanish signatures database) and GPDS (Grupo de Procesado Digital de la se?al). Local binary patterns (LBP) and Gray Level Co-occurrence Matrices (GLCM) features were calculated for robust offline signature verification system. Training and verification was done using fuzzy adaptive resonance theory-1(FART-1). The system is trained and verified for different datasets to increase the accuracy of the classifier. The results thus obtained are robust than other existing techniques. The FAR and FRR for the system is 0.74% and 0.83% respectively.

Słowa kluczowe

EN

Offline Signature Verification System; FART1 (Fuzzy Adaptive Resonance Theory); SVM Classifier (Support Vector Machine); LBP (Local Binary Patterns); GLCM (Gray Level Co-occurrence Matrices)

• Wydawca: Instytut Telekomunikacji i Informatyki Uniwersytetu Technologiczno-Przyrodniczego w Bydgoszczy
• Czasopismo: Image Processing & Communications
• Rocznik: 2017
• Tom: Vol. 22, no. 3
• Strony: 23--30
• Opis fizyczny: Bibliogr. 17 poz., rys.

Twórcy

autor

Jain C.

• Department of Computer Science, Amity University Haryana

autor

Singh P.

• Department of Electronics and Communication, Amity University Haryana

autor

Rana A.

• Amity Training & Placement Centre, Amity University Uttar Pradesh

Bibliografia

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