A Neuro-Fuzzy System Combined with Particle Swarm Optimization for Handwritten Character Recognition

• Autorzy: Chang B.-M.

Identyfikatory

DOI

10.3233/FI-2014-1080

• Języki publikacji: EN

Abstrakty

EN

A novel character recognition method, called a Neuro-Fuzzy system combined with Particle swarm optimization for Handwritten Character Recognition (NFPHCR), is proposed in this paper. The NFPHCR method integrates Recurrent Neural Network (RNN), Fuzzy Inference System (FIS), and Particle Swarm Optimization (PSO) algorithm to recognize handwritten characters. It employs the RNN to effectively extract oriented features of handwritten characters, and then, these features are applied to create the FIS. Finally, the FIS combined with the PSO algorithm can powerfully estimate similarity ratings between the recognized character and sampling characters in the character database. Experimental results demonstrate that the NFPHCR method achieves a satisfying recognition performance and outperforms other existing methods under considerations.

Słowa kluczowe

EN

neuro-fuzzy system; recurrent neural network; fuzzy inference system; particle swarm optimization (PSO); handwritten character recognition

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2014
• Tom: Vol. 133, nr 4
• Strony: 345--366
• Opis fizyczny: Bibliogr. 17 poz., rys., tab., wykr.

Twórcy

autor

Chang B.-M.

• Department of Information Management, Chienkuo Technology University, Chang-Hua, Chang-Hua 500, Taiwan

Bibliografia

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