A Real-Time Obstacle Detection Algorithm for the Visually Impaired Using Binocular Camera

2018 ◽  
pp. 1412-1419
Author(s):  
Rumin Zhang ◽  
Wenyi Wang ◽  
Liaoyuan Zeng ◽  
Jianwen Chen
Keyword(s):  
Real Time ◽  
Visually Impaired ◽  
Detection Algorithm ◽  
Obstacle Detection

scholarly journals Currency Detection for Visually Impaired Iraqi Banknote as a Study Case

2021 ◽  
Vol 12 (6) ◽  
pp. 2940-2948
Author(s):  
Raghad Raied Mahmood Et al.
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Visually Impaired ◽  
Detection System ◽  
Detection Algorithm ◽  
Geometric Transformations ◽  
Visually Impaired People ◽  
Paper Currency ◽  
Impaired People ◽  
Detection And Recognition

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.

Real-time pedestrian crossing lights detection algorithm for the visually impaired

2017 ◽  
Vol 77 (16) ◽  
pp. 20651-20671 ◽  
Author(s):  
Ruiqi Cheng ◽  
Kaiwei Wang ◽  
Kailun Yang ◽  
Ningbo Long ◽  
Jian Bai ◽  
...  
Keyword(s):  
Real Time ◽  
Visually Impaired ◽  
Detection Algorithm ◽  
Pedestrian Crossing

A REAL-TIME DETECTION ALGORITHM FOR VISION-BASED PEDESTRIAN PROTECTION

2008 ◽  
Vol 05 (01) ◽  
pp. 11-30 ◽  
Author(s):  
GUANGLIN MA ◽  
SU-BIRM PARK ◽  
ALEXANDER IOFFE ◽  
STEFAN MÜLLER-SCHNEIDERS ◽  
ANTON KUMMERT
Keyword(s):  
Real Time ◽  
Pedestrian Detection ◽  
Ground Plane ◽  
Detection Algorithm ◽  
Obstacle Detection ◽  
Low Contrast ◽  
The Road ◽  
Novel Approach ◽  
Real Time Detection ◽  
Flat Ground

This paper discusses the robust, real-time detection of stationary and moving pedestrians utilizing a single car-mounted monochrome camera. First, the system detects potential pedestrians above the ground plane by combining conventional Inverse Perspective Mapping (IPM)-based obstacle detection with the vertical 1D profile evaluation of the IPM detection result. Usage of the vertical profile increases the robustness of detection in low-contrast images as well as the detection of distant pedestrians significantly. A fast digital image stabilization algorithm is used to compensate for erroneous detections whenever the flat ground plane assumption is an inaccurate model of the road surface. Finally, a low-level pedestrian-oriented segmentation and fast symmetry search on the leg region of pedestrians is also presented. A novel approach termed Pedestrian Detection Strip (PDS) is used to improve the calculation time by a factor of six compared to conventional approaches.

scholarly journals Real Time Object Recognition and Classification using Deep Learning

2019 ◽  
pp. 355-359
Author(s):  
Kiruthiga N ◽  
Divya E ◽  
Haripriya R ◽  
Haripriya V.
Keyword(s):  
Deep Learning ◽  
Object Recognition ◽  
Object Detection ◽  
Real Time ◽  
Visually Impaired ◽  
Detection Algorithm ◽  
Indoor Environments ◽  
Wide Range ◽  
Impaired Person ◽  
First Time

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.

scholarly journals OBSTACLE DETECTION AND ELECTRONIC NAVIGATION SYSTEM FOR VISUALLY IMPAIRED PERSONS

2014 ◽  
pp. 151-153
Author(s):  
PRATEEK MISHRA ◽  
RAJ KISHOR PAL ◽  
SHIVOM KUSHWAHA ◽  
TUSHAR SRIVASTAVA ◽  
SURESH SHARMA
Keyword(s):  
Real Time ◽  
Navigation System ◽  
Visually Impaired ◽  
Detection System ◽  
Obstacle Detection ◽  
Final Destination ◽  
Visually Impaired People ◽  
The Common ◽  
Impaired Person ◽  
Visually Impaired Persons

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.

scholarly journals Design and Development of a Wearable Assistive Device Integrating a Fuzzy Decision Support System for Blind and Visually Impaired People

Micromachines ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1082
Author(s):  
Yassine Bouteraa
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Real Time ◽  
Support System ◽  
Visually Impaired ◽  
Obstacle Detection ◽  
Blind And Visually Impaired ◽  
Visually Impaired People ◽  
Impaired People

In this article, a new design of a wearable navigation support system for blind and visually impaired people (BVIP) is proposed. The proposed navigation system relies primarily on sensors, real-time processing boards, a fuzzy logic-based decision support system, and a user interface. It uses sensor data as inputs and provides the desired safety orientation to the BVIP. The user is informed about the decision based on a mixed voice–haptic interface. The navigation aid system contains two wearable obstacle detection systems managed by an embedded controller. The control system adopts the Robot Operating System (ROS) architecture supported by the Beagle Bone Black master board that meets the real-time constraints. The data acquisition and obstacle avoidance are carried out by several nodes managed by the ROS to finally deliver a mixed haptic–voice message for guidance of the BVIP. A fuzzy logic-based decision support system was implemented to help BVIP to choose a safe direction. The system has been applied to blindfolded persons and visually impaired persons. Both types of users found the system promising and pointed out its potential to become a good navigation aid in the future.

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