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计算机系统应用英文版:2013,22(6):127-131
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基于整体特征神经网络数字二次识别方法
(上海宝信软件股份有限公司, 上海 201900)
Secondary Digital Character Recognition Based on the Global Feature and BP Neural Network
(Shanghai Baosight Software Co., Ltd, Shanghai 201900, China)
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Received:December 07, 2012    Revised:January 24, 2013
中文摘要: 根据数字字符整体特征, 提出一种基于字符整体特征的Bp神经网络数字二次识别方法. 该方法首先根据Bp神经网络原理对数字字符进行预识别; 然后对预识别结果中存在混淆的字符按照字符整体特征进行二次识别, 从而准确获得识别结果. 该方法结合了神经网络非线性、自主学习特点和字符整体特征形状结构不变性特点, 有效的在低样本量情况下, 获得较高的字符识别精度.
Abstract:The secondary digital character recognition based on the character global feature and BP neural network is proposed in this paper. First of all, digital characters should be pre-recognized by the method of BP neural network, and a preliminary result can be obtained. After that, the secondary recognition to those characters which may be very close to confusing in the preliminary result should be arranged, so that, those digital characters confused can be distinguished and the better result can be reached. As a result, the method, combined with nonlinear and self-learning of the neural network, and invariance of the overall character feature of the shape and structure, can reach the high recognition accuracy on the condition of the low sample size.
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张翼成,陈欣,嵇小波,张晓荣.基于整体特征神经网络数字二次识别方法.计算机系统应用,2013,22(6):127-131
ZHANG Yi-Cheng,CHEN Xin,JI Xiao-Bo,ZHANG Xiao-Rong.Secondary Digital Character Recognition Based on the Global Feature and BP Neural Network.COMPUTER SYSTEMS APPLICATIONS,2013,22(6):127-131