Off-line Arabic/Farsi Handwritten Word Recognition Using RBF Neural Network and Genetic algorithm

摘要：

In this paper an off-line Arabic/Farsi handwritten recognition Algorithm on a subset of Farsi name is proposed. In this system, There is no sub-word segmentation phase. Script database includes 3300 images of 30 Farsi common names. The features are wavelet coefficients extracted from smoothed word image profiles in four standard directions. The Centers of competitive layer of RBF neural network have been determined by combining GA and K_Means clustering algorithm. Weights of supervised layer has been trained by using LMS rule and the distances of feature vector of each sample to the centre of RBF network have been computed based on warping function. Experimental results show advantages of this method in field of handwriting recognition.

关键词： Farsi Handwritten recognition genetic algorithm K_Means algorithm RBF neural network and wavelet transform

作者: Zahra bahmani Fatemh Alamdar Reza Azmi Saman Haratizadeh

作者单位: Computer department Alzahra University Tehran, Iran Department of Computer Engineering Sharif University Tehran, Iran

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 352-357

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）