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Currency Recognition System for Blind people using ORB Algorithm

机译:ORB算法的盲人货币识别系统

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Despite the quickly expanding utilization of Master cards and other electronic types of payment, money is still broadly utilized for ordinary exchanges because of its convenience. However, the visually impaired people may suffer from knowing each currency paper apart. Currency Recognition Systems (CRS) can be used to help blind and visually impaired people who suffer from monetary transactions. In this paper, a Currency Recognition System based on Oriented FAST and rotated BRIEF (ORB) algorithm is proposed. The ORB is based on the FAST detector and the visual descriptor BRIEF (Binary Robust Independent Elementary Features). Its aim is to provide a fast and efficient alternative to Local Scale-Invariant Features (SIFT). The proposed system is applied to Egyptian paper currencies including six kinds of currency papers. Initially, some pre-processing operations are performed on a given currency paper input image. Then, important ROI is extracted from the background. The ORB Algorithm is used for a feature detection and description the input image. Finally, Hamming Distance is used for matching binary descriptors obtained from feature extraction stage. The proposed method is compared with another system (CRSFVI). The experimental results showed that the proposed system can be used in real-world scenarios to recognize unknown currency paper image with a higher accuracy of 96 % and a shorter running time of 0.682 s when compared with the CRSFVI system.
机译:尽管万事达卡和其他电子支付方式的使用迅速扩大,但由于其方便性,货币仍广泛用于普通交易所。但是,视障人士可能会因分别了解每种纸币而遭受痛苦。货币识别系统(CRS)可用于帮助遭受货币交易困扰的盲人和视障人士。提出了一种基于方向FAST和旋转BRIED(ORB)算法的货币识别系统。 ORB基于FAST检测器和视觉描述符Brief(二进制鲁棒独立基本特征)。其目的是提供一种快速有效的替代局部尺度不变特征(SIFT)的方法。拟议的系统适用于埃及纸币,包括六种纸币。最初,对给定的货币纸币输入图像执行一些预处理操作。然后,从背景中提取重要的ROI。 ORB算法用于特征检测和描述输入图像。最后,汉明距离用于匹配从特征提取阶段获得的二进制描述符。将该方法与另一个系统(CRSFVI)进行了比较。实验结果表明,与CRSFVI系统相比,该系统可以在真实场景下识别未知货币纸币图像,准确率高达96%,运行时间仅为0.682s。

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