使用人工神经网络的南印度语言手写数字识别系统

2015 Eighth International Conference on Contemporary Computing (IC3) Pub Date : 2015-08-20 DOI:10.1109/IC3.2015.7346665

Leo Pauly, Rahul D. Raj, B. Paul

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引用次数: 6

摘要

本文提出了一种利用人工神经网络(ANN)和梯度直方图(HOG)特征识别南印度语手写数字的新方法。包含手写数字的文档图像被光学扫描并分割成孤立数字的单个图像。然后从这些图像中提取HOG特征并应用于人工神经网络进行识别。该系统识别数字的总体准确率为83.4%。

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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Hand written digit recognition system for South Indian languages using artificial neural networks

In this paper a novel approach for recognition of handwritten digits for South Indian languages using artificial neural networks (ANN) and Histogram of Oriented Gradients (HOG) features is presented. The images of documents containing the hand written digits are optically scanned and are segmented into individual images of isolated digits. HOG features are then extracted from these images and applied to the ANN for recognition. The system recognises the digits with an overall accuracy of 83.4%.

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2015 Eighth International Conference on Contemporary Computing (IC3)

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