基于改进梯度方向直方图的人民币识别(英文)

深圳市激光工程重点实验室,深圳大学电子科学与技术学院, 广东省高校先进光学精密制造技术重点实验室,深圳 518060

红外图像; 人民币纸币识别; 梯度方向直方图; 支持向量机; Fisher准则; 精密鉴伪; 图像特征提取

Improved histograms of oriented gradients for Chinese RMB currency recognition
Hu Xuejuan, Ruan Shuangchen, Guo Chunyu, and Liu Chengxiang

Hu Xuejuan, Ruan Shuangchen, Guo Chunyu, and Liu ChengxiangShenzhen Key Laboratory of Laser Engineering, College of Electronic Science and Technology, Key Laboratory of Advanced Optical Precision Manufacturing Technology of Guangdong Higher Education Institutes, Shenzhen University, Shenzhen 518060, P.R.China

infrared image; Chinese RMB currency recognition; histogram of oriented gradients; support vector machine; Fisher criterion; precision counterfeit detection; image feature extraction

DOI: 10.3724/SP.J.1249.2014.05487

备注

提出一种基于改进梯度方向直方图和支持向量机分类器的人民币识别方法.利用人民币红外图像中斑马线特征进行真伪识别,通过Fisher准则进行特征块选择实现梯度方向直方图特征的降维.针对斑马线防伪图案进行实验. 结果表明,该方法能克服红外图像中的背景干扰和噪声,得到较好鉴伪结果.

This paper presents a method to improve the histograms of oriented gradient descriptors and support vector machine classifier for Chinese RMB currency recognition. The zebra-stripe pattern of the infrared images of RMB paper currency was used for real and counterfeit classification. The dimension of histograms of oriented gradient features is decreased by feature block selection based on the Fisher criterion. Several experiments on zebra-stripe pattern recognition were conducted, and the proposed method shows its robustness against background interference and noise.

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