基于支持向量机的纸币号码识别新算法

S. Gai, Guowei Yang, S. Zhang, M. Wan
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引用次数: 6

摘要

纸币序列号的检测是商业交易中的一项重要工作。本文提出了一种新的钞票号码识别方法。对每张钞票图像进行预处理,定位钞票号码图像的位置。将数字图像分成互不重叠的分区,并将各分区的平均灰度值作为特征向量进行识别。利用半确定规划方法得到了最优核函数。实验结果表明,该方法优于MASK、BP、HMM和单个SVM分类器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New Banknote Number Recognition Algorithm Based on Support Vector Machine
Detecting the banknote serial number is an important task in business transaction. In this paper, we propose a new banknote number recognition method. The preprocessing of each banknote image is used to locate position of the banknote number image. Each number image is divided into non-overlapping partitions and the average gray value of each partition is used as feature vector for recognition. The optimal kernel function is obtained by the semi-definite programming (SDP). The experimental results show that the proposed method outperforms MASK, BP, HMM, Single SVM classifiers.
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