Fuzzy Logic Based Perceptual Image Hashing Algorithm in Malaysian Banknotes Detection System for the Visually Impaired

Visually impaired persons have difficulty in business that dealing with banknote. This paper proposed a Malaysian banknotes detection system using image processing technology and fuzzy logic algorithm for the visually impaired. The Malaysian banknote reader will first capture the inserted banknote image, sending it to the cloud server for image processing via Wi-Fi medium. The cloud server is established to receive the banknote image sending from the banknote reader, processing them using perceptual hashing based image searching and fuzzy logic algorithm, then return the detected banknote’s value results back to the banknote reader. The banknote reader will display the results in terms of voice message played on the mini speaker attached on it, to allow visually impaired persons knowing the banknote’s value. This hardware mechanism reduces the size and costs for the banknote reader carried by the visually impaired persons. Experimental results showed that this Malaysian banknotes detection system reached an accuracy beyond 95% by running test on 600 different worn, torn and new Malaysian banknotes. After the banknote image being taken by the banknote reader’s camera, the system able to detect the banknote value in about 480 mili-seconds to 560 mili-seconds for a single sided banknote recognition. The banknotes detection speed was also comparable with human observers reading banknotes, with the response of 1.0908 second per banknote slight difference reading time. The IoT and image processing concepts were successfully blended and it provides an alternative to aid the visually impaired person their daily business transaction activities in a better way

Euro Banknote Recognition System for Blind People

[EN] This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter) dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF) technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively.The work was supported by the project from the Generalitat Valenciana under the number GV/2014/015-Emergency projects.Dunai, L.; Chillarón-Pérez, M.; Peris Fajarnes, G.; Lengua, I. (2017). Euro Banknote Recognition System for Blind People. Sensors. 17(1)(184):1-14. https://doi.org/10.3390/s17010184S11417(1)18

Banknote Recognition for Visually Impaired People (Case of Ethiopian note)

Currency is used almost everywhere to facilitate business. In most developing countries, especially the ones in Africa, tangible notes are predominantly used in everyday financial transactions. One of these countries, Ethiopia, is believed to have one of the world highest rates of blindness (1.6%) and low vision (3.7%). There are around 4 million visually impaired people; With 1.7 million people being in complete vision loss. Those people face a number of challenges when they are in a bus station, in shopping centers, or anywhere which requires the physical exchange of money. In this paper, we try to provide a solution to this issue using AI/ML applications. We developed an Android and IOS compatible mobile application with a model that achieved 98.9% classification accuracy on our dataset. The application has a voice integrated feature that tells the type of the scanned currency in Amharic, the working language of Ethiopia. The application is developed to be easily accessible by its users. It is build to reduce the burden of visually impaired people in Ethiopia.Comment: 3 pages, 2 figures, Machine Learning for Development Workshop at NeurIPS 202

Iranian cashes recognition using mobile

In economical societies of today, using cash is an inseparable aspect of human life. People use cashes for marketing, services, entertainments, bank operations and so on. This huge amount of contact with cash and the necessity of knowing the monetary value of it caused one of the most challenging problems for visually impaired people. In this paper we propose a mobile phone based approach to identify monetary value of a picture taken from cashes using some image processing and machine vision techniques. While the developed approach is very fast, it can recognize the value of cash by average accuracy of about 95% and can overcome different challenges like rotation, scaling, collision, illumination changes, perspective, and some others.Comment: arXiv #13370

Handicapping currency design: counterfeit deterrence and visual accessibility in the United States and abroad

Despite the increasing use of electronic payments, currency retains an important role in the payments system of every country. Two aspects of currency usage drive currency design worldwide: deterring counterfeiting and making paper currency accessible to the visually impaired. Further, among the world's currencies, only U.S. banknotes are widely owned and used in transactions outside their country of issue (although the euro also has some external circulation). In this article, we compare and contrast major currencies and their design features. We conclude that the designs of the two most widely used currencies in the world-the U.S. dollar and the euro-have successfully deterred counterfeiting; data on other currencies are not public. We also conclude that, among the world's major currencies, U.S. banknotes have the fewest features to assist the visually impaired.Paper money design ; Coinage ; Counterfeits and counterfeiting

Currency design in the United States and abroad: counterfeit deterrence and visual accessibility

Despite the increasing use of electronic payments, currency retains an important role in the payment system of every country. In this article, the authors compare and contrast trade-offs among currency design features, including those primarily intended to deter counterfeiting and those to improve usability by the visually impaired. The authors conclude that periodic changes in the design of currency are an important aspect of counterfeit deterrence and that currency designers worldwide generally have been successful in efforts to deter counterfeiting. At the same time, currency designers have sought to be sensitive to the needs of the visually impaired. Although trade-offs among goals sometimes have forced compromises, new technologies promise banknotes that are both more difficult to counterfeit and more accessible to the visually impaired. Among the world's currencies, U.S. banknotes are the notes most widely used outside their country of issue and thus require special consideration.Paper money design - United States ; Money

Image Based Ringgit Banknote Recognition for Visually Impaired

Visually impaired people face a number of difficulties in order to interact with the environment because most of the information encoded is visual. Visual impaired people faced a problem in identifying and recognizing the different currency. There are many devices available in the market but not acceptable to detect Malaysian ringgit banknote and very pricey. Many studies and investigation have been done in introducing automated bank note recognition system and can be separated into vision based system or sensor based system. The objective of this project was to develop an automated system or algorithm that can recognize and classify different Ringgit Banknote for visually impaired person based on banknote image. In this project, the features extraction of the RGB values in six different classes of banknotes (RM1, RM5, RM10, RM20, RM 50, and RM100) was done by using Matlab software. Three features called RB, RG and GB extracted from the RGB values were used for the classification algorithms such as k-Nearest Neighbors (k-NN) and Decision Tree Classifier (DTC) for recognizing each classes of banknote. Ten-fold cross validation was used to select the optimized k-NN and DTC, which was based on the smallest cross validation loss. After that, the performance of optimize k-NN and DTC model was presented in confusion matrix. Result shows that the proposed k-NN and DTC model managed to achieve 99.7% accuracy with the RM50 class causing major reduction in performance. In conclusion, an image based automated system that can recognize the Malaysian banknote using k-NN and DTC classifier has been successfully developed

Robust and Effective Banknote Recognition Model for Aiding Visual Impaired People

Visual disabled Ethiopians find great difficulty in recognizing banknotes. Each Ethiopian banknote has an identical feel, with no Braille markings, irregular edges, or other tangible features that make it easily recognizable by blind persons. In Ethiopia, there's only one device available that will assist blind people to acknowledge their notes. Internationally, there are devices available; however, they're expensive, complex, and haven't been developed to cater to Ethiopian currency. Because of these facts, visually impaired people may suffer from recognizing each folding money. This fact necessitates a higher authentication and verification system that will help visually disabled people to simply identify and recognize the banknotes. This paper presents a denomination-specific component-based framework for a banknote recognition system. Within the study, the dominant color of the banknotes was first identified and so the exclusive feature for every denomination-specific ROI was calculated. Finally, the Colour-Momentum, dominant color, and GLCM features were calculated from each denomination-specific ROI. Designing the recognition system by thereby considering the denomination-specific ROI is simpler as compared to considering the entire note in collecting more class-specific information and robust in copying with partial occlusion and viewpoint changes. The performance of the proposed model was verified by using a larger dataset of which containing banknotes in several conditions including occlusion, cluttered background, rotation, and changes of illumination, scaling, and viewpoints. The proposed algorithm achieves a 98% recognition rate on our challenging datasets

The overview of investigation in the field of banknote design for visually impaired people

Abstract This essay aims to elaborate the technology when it comes to banknote making for visually impaired members of the society. The visually impaired are divided in three subgroups: color-blind, partially sighted and blind people. Their first needs are useful denomination features rather than security features, as they help them in determining a banknote’s value. This study provides a historical overview of banknote design features for the visually impaired. Furthermore, it looks into the methodology of banknote tests for the color-blind, showing images of how the color-blind experience the euro banknotes. Two features are needed for every subgroup of the visually impaired to establish the banknote’s value; one is not reliable. These two features are dedicated firstly to the relevant user group, but will also be used by others, including people with normal vision

Money bill technology of tactile recognition engravings for visually impaired

Summary This essay aims to elaborate the technology when it comes to banknote making for visually impaired members of the society. The visually impaired are divided in three subgroups: colour-blind, partially sighted and blind people. Their first needs are useful denomination features rather than security features, as they help them in determining a banknote’s value. This study provides a historical overview of banknote design features for the visually impaired. Furthermore, it looks into the methodology of banknote tests for the colour-blind, showing images of how the colour-blind experience the euro banknotes. Two features are needed for every subgroup of the visually impaired to establish the banknote’s value; one is not reliable. These two features are dedicated firstly to the relevant user group, but will also be used by others, including people with normal vision