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Feature Extraction for Paper Currency Recognition

机译:纸币识别的功能提取

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This paper proposes a new technique for paper currency recognition. In this technique, three characteristics of paper currencies including size, color and texture are used in the recognition. By using image histogram, plenitude of different colors in a paper currency is computed and compared with the one in the reference paper currency. The Markov chain concept has been employed to model texture of the paper currencies as a random process. The method proposed in this paper can be used for recognizing paper currencies from different countries. In this method, using only one intact example of paper currency from each denomination is enough for training the system. We tested this method on more than 100 denominations from different countries, and the system was able to recognize 95% of data, correctly.
机译:本文提出了一种新的纸币识别技术。在这种技术中,在识别中使用包括尺寸,颜色和纹理的纸币的三种特征。通过使用图像直方图,计算纸币中不同颜色的宽度,并与参考纸币中的不同颜色进行比较。马尔可夫链概念已被用于将纸币的纹理模拟为随机过程。本文提出的方法可用于识别来自不同国家的纸币。在这种方法中,仅使用每个面额的一个完整的纸币的例子足以训练系统。我们在不同国家的100多个面对数上测试了这种方法,该系统能够正确地识别95%的数据。

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