Accessible Shopping System for Blind and Visually Impaired Individuals

Self-Dependency of disabled persons is very important in their daily lives. This is a cost effective prototype system that help blind persons to shop independently. This paper presents a camera-based label reader for blind persons to read names of labels on the products. The proposed framework can be classified as image capturing, data processing audio output. In Image capturing web Camera is use to capture the image of object or product packaging and captured image is send to the image processing Platform. In Data processing the image is processed internally and the text will get filtered from the image. Finally, the filtered texts are output to blind users in the form voice. The Tesseract library is used to get the plain text from text region and flite library is used to get audio output. This proposed framework is implemented using Raspberry Pi board

Comparative analysis of computer-vision and BLE technology based indoor navigation systems for people with visual impairments

Background: Considerable number of indoor navigation systems has been proposed to augment people with visual impairments (VI) about their surroundings. These systems leverage several technologies, such as computer-vision, Bluetooth low energy (BLE), and other techniques to estimate the position of a user in indoor areas. Computer-vision based systems use several techniques including matching pictures, classifying captured images, recognizing visual objects or visual markers. BLE based system utilizes BLE beacons attached in the indoor areas as the source of the radio frequency signal to localize the position of the user. Methods: In this paper, we examine the performance and usability of two computer-vision based systems and BLE-based system. The first system is computer-vision based system, called CamNav that uses a trained deep learning model to recognize locations, and the second system, called QRNav, that utilizes visual markers (QR codes) to determine locations. A field test with 10 blindfolded users has been conducted while using the three navigation systems. Results: The obtained results from navigation experiment and feedback from blindfolded users show that QRNav and CamNav system is more efficient than BLE based system in terms of accuracy and usability. The error occurred in BLE based application is more than 30% compared to computer vision based systems including CamNav and QRNav. Conclusions: The developed navigation systems are able to provide reliable assistance for the participants during real time experiments. Some of the participants took minimal external assistance while moving through the junctions in the corridor areas. Computer vision technology demonstrated its superiority over BLE technology in assistive systems for people with visual impairments. - 2019 The Author(s).Scopu