Salem Turki Khaled, Wong Wai Kit, Min Thu Soe, Wong Eng Kiong
Faculty of Engineering and Technology, Multimedia University, BKT Beruang, Melaka, 75450, Malaysia.
F1000Res. 2022 Apr 13;10:1098. doi: 10.12688/f1000research.58446.2. eCollection 2021.
Visually impaired persons face challenges in running business activities, especially in handling banknotes. Malaysia researchers had proposed some Ringgit banknotes recognition systems to aid visually impaired persons recognize and classify Ringgit banknotes. However, these electronic banknote readers can only recognize Malaysian Banknotes' Ringgit value, they have no counterfeit detection features. The purpose of this study is to develop a banknote reader that not only can help visually impaired persons recognize the banknote value, but also to detect the counterfeit of the banknote, safeguarding their losses. This paper proposed a Malaysian banknote reader using backlight mechanism and image processing techniques to read and detect counterfeit for one Ringgit and five Ringgit Malaysian banknotes. The developed handheld banknote reader used visual type sensor to capture banknote image, passed to raspberry pi controller to perform image processing on banknote value and the extracted watermarks features. The developed image processing algorithm will trace out the region of interests: 1)see-thru windows, 2)Crescent and Star, 3)Perfect see though register and detect the watermarks features accordingly. The processed result will be passed back to the handheld banknote reader and broadcast on an attached mini speaker to aid the visually impaired understand the holding banknote, whether it is a real one Ringgit, real five Ringgit or none of them. The experimental result shown by this approach able to accomplish numerous round of banknote reading attempts with successful outcomes. Confusion matrix is further employed to study the performance of the banknote reader, in terms of true positive, true negative, false positive and false negative. Details analysis had been focused on the critical false positive cases (predicted real banknote and actually is fake banknote) and false negative cases (predicted fake banknote and it is actually real banknote).
视障人士在开展商业活动时面临挑战，尤其是在处理纸币方面。马来西亚的研究人员提出了一些林吉特纸币识别系统，以帮助视障人士识别和分类林吉特纸币。然而，这些电子纸币阅读器只能识别马来西亚纸币的林吉特价值，它们没有防伪检测功能。本研究的目的是开发一种纸币阅读器，它不仅可以帮助视障人士识别纸币价值，还能检测纸币的真伪，以保护他们的损失。本文提出了一种利用背光机制和图像处理技术的马来西亚纸币阅读器，用于读取和检测一林吉特和五林吉特马来西亚纸币的真伪。所开发的手持式纸币阅读器使用视觉型传感器捕获纸币图像，将其传递给树莓派控制器，以对纸币价值和提取的水印特征进行图像处理。所开发的图像处理算法将追踪出感兴趣的区域：1）透视窗，2）新月和星星，3）完美透视对齐，并相应地检测水印特征。处理结果将传回手持式纸币阅读器，并通过连接的迷你扬声器进行播报，以帮助视障人士了解手中持有的纸币，无论是真的一林吉特、真的五林吉特还是都不是。该方法的实验结果表明，能够成功完成多轮纸币读取尝试。进一步使用混淆矩阵来研究纸币阅读器的性能，包括真阳性、真阴性、假阳性和假阴性。详细分析集中在关键的假阳性情况（预测为真纸币但实际上是假纸币）和假阴性情况（预测为假纸币但实际上是真纸币）上。
