AN OFF-LINE TEXT-INDEPENDENT PERSIAN WRITER IDENTIFICATION METHOD

作者：Helli Behzad^*; Moghaddam Mohsen Ebrahimi

来源：International Journal on Artificial Intelligence Tools, 2011, 20(3): 489-509.

DOI：10.1142/S0218213011000243

• Writer identification
• texture analysis
• Gabor filter
• neural networks
• Persian Language

The behavioral-biometrics methods of writer identification and verification have been considered as a research topic for many years. However, many writer identification and verification methods have been designed based on English handwriting properties, but because of many differences between English and Persian handwriting and the challenges facing Persian handwriting analysis, designing such methods has many interests in Persian yet. In this paper, we have presented a fully text-independent and texture based method for identifying writers of Persian handwritten documents. As a result of special properties of Persian handwriting, a modified version of Gabor filter that is called Extended Gabor (XGabor) filter has been used to extract the features. An MLP (Multi Layer Perceptron (Node)) neural network and a K-NN classifier have been employed to classify the extracted features. In the evaluation phase, an exhaustive database of Persian handwritten documents was prepared and the method applied on. The experimental results showed that the accuracy of proposed method is about 97% and it is competitive with others. We believe that the proposed method may be extended to identify writers in other languages by adjusting some parameters.

• 出版日期2011-6