基于退化四元小波变换的纸币识别

针对如何提取纸币图像特征和提高识别率的问题,综合利用退化四元小波变换具有的相位特性,提出一种基于退化四元小波变换的纸币识别方法.该方法首先对采集的纸币图像进行倾斜校正和边缘检测,然后运用退化四元小波对纸币图像进行分解操作,并对分解系数进行统计分析,将每个分解子带系数的能量和标准差作为该纸币图像的特征向量,最后将支持向量机作为分类器对纸币图像进行识别.本文方法在资源约束的嵌入式清分系统上实现,实验结果表明采用本文提出的算法突破了传统纸币识别系统识别率很难再提高的瓶颈,同时能够满足清分系统的实时性要求.

Banknote Recognition Based on Reduced Quaternion Wavelet Transform

A new banknote classification method is proposed by using phase concept of reduced quaternion wavelet transform (RQWT) to improve the banknote recognition rate and feature extraction. Banknote is preprocessed including edge detection and slant correction. And image is decomposed by reduced quaternion wavelet. The statistical characteristics of the decomposition coefficients are used as features of the banknote image for classification. Finally, the support vector machine is applied as classifier in the banknote classification system. The experimental results show that the proposed method can obtain better results compared with other conventional methods and satisfy the real time requirements.