Real-time Bangladeshi Currency Detection System for Visually Impaired Person

Author(s):  
Md. Ferdousur Rahman Sarker ◽  
Md. Israfil Mahmud Raju ◽  
Ahmed Al Marouf ◽  
Rubaiya Hafiz ◽  
Syed Akhter Hossain ◽  
...  
Author(s):  
PRATEEK MISHRA ◽  
RAJ KISHOR PAL ◽  
SHIVOM KUSHWAHA ◽  
TUSHAR SRIVASTAVA ◽  
SURESH SHARMA

In This Paper we present a real time domain obstacle detection system for the visually impaired persons to improve their mobility in daily life with the help of obstacle detection sensor installed in their walking stick .System is having a lower cost so it is easily purchasable so it can have a major significance in life of visually impaired persons. This Paper proposes a system to detect any object attached to the floor regardless to their height [1]. Obstacle on the floor in the front of user can be reliably detected in real time using the proposed system implemented by the IR sensor installed on the walk stick of the visually impaired person. Project also contains a navigation system for visually impaired persons to make the life of such persons easier up to some extent. This project is suited for the area where the possibility of blind person is high (like blind school, college)[6]. For transport facility of blind we have first decided the common bus roots of blind then we have placed RF tag to all those buses with unique code. At the second side we have placed RF reader, microcontroller and voice processor. The RF reader receive unique code, microcontroller process this code with defined code, if match found, voice processor get activated and starts speaking bus name, initial destination and final destination. The obstacle detection is also included in the project with voice. The system aims at increasing the mobility of visually impaired people by offering new sensing abilities.


Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 941
Author(s):  
Rakesh Chandra Joshi ◽  
Saumya Yadav ◽  
Malay Kishore Dutta ◽  
Carlos M. Travieso-Gonzalez

Visually impaired people face numerous difficulties in their daily life, and technological interventions may assist them to meet these challenges. This paper proposes an artificial intelligence-based fully automatic assistive technology to recognize different objects, and auditory inputs are provided to the user in real time, which gives better understanding to the visually impaired person about their surroundings. A deep-learning model is trained with multiple images of objects that are highly relevant to the visually impaired person. Training images are augmented and manually annotated to bring more robustness to the trained model. In addition to computer vision-based techniques for object recognition, a distance-measuring sensor is integrated to make the device more comprehensive by recognizing obstacles while navigating from one place to another. The auditory information that is conveyed to the user after scene segmentation and obstacle identification is optimized to obtain more information in less time for faster processing of video frames. The average accuracy of this proposed method is 95.19% and 99.69% for object detection and recognition, respectively. The time complexity is low, allowing a user to perceive the surrounding scene in real time.


Author(s):  
Raghad Raied Mahmood Et al.

It is relatively simple for a normal human to interpret and understand every banknote, but one of the major problems for visually impaired people are money recognition, especially for paper currency. Since money plays such an important role in our everyday lives and is required for every business transaction, real-time detection and recognition of banknotes become a necessity for blind or visually impaired people For that purpose, we propose a real-time object detection system to help visually impaired people in their daily business transactions. Dataset Images of the Iraqi banknote category are collected in different conditions initially and then, these images are augmented with different geometric transformations, to make the system strong. These augmented images are then annotated manually using the "LabelImg" program, from which training sets and validation image sets are prepared. We will use YOLOv3 real-time Object Detection algorithm trained on custom Iraqi banknote dataset for detection and recognition of banknotes. Then the label of the banknotes is identified and then converted into audio by using Google Text to Speech (gTTS), which will be the expected output. The performance of the trained model is evaluated on a test dataset and real-time live video. The test results demonstrate that the proposed method can detect and recognize Iraqi paper money with high mAP reaches 97.405% and a short time.


Author(s):  
Kiruthiga N ◽  
Divya E ◽  
Haripriya R ◽  
Haripriya V.

Navigation in indoor environments is highly challenging for visually impaired person, particularly in spaces visited for the first time. Various solutions have been proposed to deal with this challenge. In this project consider as the real time object Recognition and classification using deep learning algorithms. Object detection mainly deals with identification of real time objects such as people, animals, and objects. Object detection algorithm uses a wide range of image processing applications for extracting the object's desired portion. This enables one to identify the objects and calculate the accuracy of the object and deliver through voice. Using this information, the system determines the user's trajectory and can locate possible obstacles in that route.


A visually impaired person can identify the shape of an object by the sense of touch but to recognize the colour and pattern of a textile would require the assistance of a helper. The paper proposes a system which can assist a person with visual disability in real time. The proposed system will be able to detect both the colour as well as pattern of the textile. For pattern detection, Hough line transform is implemented and for colour detection k-means clustering algorithm is implemented. Both used together can detect the colour and pattern, thus making the user independent of assistance of another. The system can detect patterns such as plain, vertical stripes, horizontal stripes, diagonal pattern and checks. Also the system detects the entire range of colours and the colour range is not limited. The main scope is to build an independent system which will be self-sufficient. The system also converts the identified data to audio for assistance to the visually impaired.


It is realized that innovative progressions are expanding at a quicker pace. In any case, the usage of these innovations is less in different parts. It is realized that the general population of nowadays need help for doing a few works when they were matured. .It is troublesome for visually impaired individuals to recognize these articles whenever lostinside a home. But since of these actualities, we may encounter different pressure and issues identified with the loss of those items for individuals. So, we propose a framework where we candistinguishthelostarticleswiththeassistanceofourproposedfram eworkutilizingImagehandlingprocedures.Thatadditionallyreadyto supporttheindividualdependentontheface recognized and confine or personal the passage of obscure people. The current frameworkdistinguishesthelostarticleswiththeassistanceofGPS.Ye t,theuseoffaceacknowledgement for individual recognizable proof by robots is not being used. It doesn't give proficient yield. This causes different slack in the circuit. So we propose a framework to upgrade the item following.


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