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Bill Denomination Recognition Using Digital Image Analysis

机译:使用数字图像分析的票据面额识别

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This research talks about a system that can recognize denomination of bills particularly in the country of the Philippines using digital image analysis. The system can be used in Cash Accept Machines in which people who are cash depositors interact with machine directly. The initial algorithm of the system has some steps such as; grayscaling, binarization using Otsu method, region of interest, and then optical character recognition. Based on the results, the accuracy of the system is 96.67% for denomination recognition and 98.59% for digit recognition. To reach to the highest accuracy of 100%, based on experimental results and the digits used in Philippines’ bills, the researchers add a conditional step to the algorithm in which the digits change to other digits. From software view, the researchers used Linux Ubuntu 18 as operating system, Python as programming language and OpenCV as library. From hardware view, the system was implemented in a computer having CPU Core i5, 4GB RAM and 1GB VGA.
机译:这项研究讨论的是一种可以使用数字图像分析识别钞票面额的系统,尤其是在菲律宾国家。该系统可以在现金接受机中使用,在该机中,作为现金存款人的人可以直接与机器进行交互。系统的初始算法包括以下步骤:灰度,使用Otsu方法进行二值化,感兴趣的区域,然后进行光学字符识别。根据结果​​,该系统的面额识别准确度为96.67%,数字识别准确度为98.59%。为了达到100%的最高准确度,根据实验结果和菲律宾钞票中使用的数字,研究人员在算法中增加了一个条件步骤,使数字变为其他数字。从软件角度来看,研究人员使用Linux Ubuntu 18作为操作系统,使用Python作为编程语言,使用OpenCV作为库。从硬件角度来看,该系统是在具有CPU Core i5、4GB RAM和1GB VGA的计算机中实现的。

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