Indian Journal of Science and Technology
Year: 2020, Volume: 13, Issue: 16, Pages: 1612-1618
Muhammad Abbas Khan1∗, Dr. Muhammad Zubair Khan2 , Sohaib Ehsan Bazai1 , Syed Owais Ahmed1 , Hayat Khan1 , Nasir Ejaz1 , Naqeeb ullah1
1 Department of Electrical Engineering, FICT, BUITEMS, Pakistan
2 Department of Mathematical Sciences, FABS, BUITEMS, Pakistan
Muhammad Abbas Khan
Department of Electrical Engineering, FICT, BUITEMS, Pakistan
Email: [email protected]
Received Date:27 March 2020, Accepted Date:24 April 2020, Published Date:07 June 2020
Objectives/Aim: The present paper deals with building a smart assistant with the aim of assisting the visually impaired people in mobility with confidence by realizing the nearby obstacles and also implement image processing techniques to recognize people. Methods: We use Raspberry Pi 4 which has increased computing performance and is interfaced to the picamera, GPS and GSM modules. Arduino pro mini with buzzer, ultrasonic sensors and vibration motors are used for obstacle detection. Certain libraries important for image processing are used such as OpenCV, Dlib, face detection (Haar cascades, HOG + Linear SVM, or CNNs), espeak for converting text to speech. Programming was implemented through Python and Arduino compiler. Findings: Analysis was carried out using the proposed system for the blind and visually impaired people who could move around comfortably with confidence and were also able to detect objects and recognize people. Hence the proposed system removes the use for the cumbersome white cane in exchange for small and handy modules which can be used in the form of wearables mounted on shoulders, hands and legs to detect the obstacles from multiple directions and provide for a comfortable wear. It was determined that the Raspberry pi 4 was incapable of running CNN detection for which ideally computer GPU was required, so HOG detection method was used instead. Application/Improvements: This project can be implemented mainly in the commercial field of helping visually impaired people with poor eyesight or being completely blind. Industrial applications can be devised and enhanced like robots and machineries along with Security, Identifying and Tracking.
Keywords: Face Recognition; Obstacle Detection; Open Source Computer Vision (OpenCV); Deep Learning; Histogram of Oriented Gradients (HOG); Support Vector Machine (SVM); Convolutional Neural Network (CNN)
© 2020 Khan, Khan, Bazai, Ahmed, Khan, Ejaz, ullah. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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