HOMER: Cryptography based Currency Detection System for Visually Impaired People
Hrishikesh Jangir, Nikunj Raghav, Nikhil Kashyap, Poonam Tanwar, Brijesh Kumar · 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT) · 2020
Currency is of great importance in everyday life and is the lifeline of every transaction. Even with the vast utilization of cards and other electronic payments, paper currency is still extensively used because of its convenience. There are around 10 different types of notes in Indian currency, and every banknote is different from other in dimensions. For instance, colour and pattern, size of the note, and so on. Most of the people practice the usage of Master Cards and Electronic payment and where the money is accepted for ordinary exchanges because of its accessibility. Visually impaired people undergo the difficulty of differentiating the currency papers. Currency Recognition System (CRS) may be effective for the blind and visually impaired people during the process of currency trade. In the proposed method a Currency Recognition System based on Accelerated- KAZE(AKAZE) algorithm is suggested, Accelerated-KAZE (AKAZE) algorithm is based around the concept of nonlinear diffusion filtering. It aims to provide an accurate and efficient alternative to Oriented FAST and rotated BRIEF(ORB). The proposed system is applied to Indian paper currencies. Originally, some of the preprocessing procedures are conducted on the input paper currency image. Then, colour mapping of the input image is done to distinguish colour components from depth. After this, the ROI (Region of Interest) is the essence of the input image. The AKAZE Algorithm is used to find key points and descriptors of the input image. Finally. the detection of currency is done by using brute force matcher technique, it matches descriptors & keypoints of the input image with every descriptor stored in dataset using Hamming Distance Calculation. In a real-world situation, the proposed system playa a vital role in identifying currency images with greater accuracy of 90 % which is achieved and determined. This proposed system aims to make the life of visually impaired people easier.