Enhanced Bangla Character Recognition Using ANN

Piu Upadhyay, Sumana Barman, D. Bhattacharyya, M. Dixit
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引用次数: 4

Abstract

This paper describes how the Bangla characters are processed, trained and then recognized with the use of a neural network. The size and the font used for the characters are similar in both training and classification of the network. The images are first converted into grayscale and then to binary images. These images are then scaled to fit a pre-defined area. By extracting the characteristics points we get the feature vectors, which is simply a series of 0s and 1s of fixed length. Finally, an Artificial Neural Network is chosen for the training and classification process. It has been noticed that recognition decreases due to presence of touching characters in the text. So recognition is done here with isolated printed characters.
利用人工神经网络增强孟加拉语字符识别
本文描述了如何利用神经网络对孟加拉语字符进行处理、训练和识别。在网络的训练和分类中,字符的大小和字体都是相似的。首先将图像转换为灰度图像,然后再转换为二值图像。然后将这些图像缩放以适应预定义的区域。通过提取特征点得到特征向量,特征向量就是一串固定长度的0和1。最后,选择人工神经网络进行训练和分类。人们已经注意到,由于文本中存在触摸字符,识别会降低。所以识别是用孤立的打印字符来完成的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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