中文说明：手写印地语数字识别在阿拉伯东部国家发挥着重要作用，特别是在阿拉伯银行支票的礼节金额。本文提出了一种有效的脱机手写印地语数字识别系统，并利用多层感知器神经网络（MLP）进行了开发。实现的系统识别分离手写印地语数字扫描使用扫描仪。该系统已经设计、实现和测试成功。采用误差反向传播算法对MLP网络进行训练。分析表明，通过做一些增强可以提高识别率。该系统在1000幅图像样本上进行了训练，并在不同年龄段的不同用户编写的600幅图像样本上进行了测试。样本在进入神经网络之前进行扫描和预处理
English Description：
Handwritten Hindi digit recognition plays an important role in eastern Arab countries especially in the courtesy amounts of Arab bank checks. In this paper, we proposed an efficient offline handwritten Hindi digits recognition system and developed using Multilayer Perceptron Neural Network (MLP). The implemented system recognizes separated handwritten Hindi digits scanned using a scanner. The system has been designed, implemented and tested successfully. The error backpropagation algorithm has been used to train the MLP network. An analysis shows increasing in the recognition rate by doing some enhancements. The proposed system has been trained on samples of 1000 images and tested on samples of 600 images written by different users selected from different ages. The samples were scanned and preprocessed before entering the Neural Network for recognition.