Blind Assistive System based on Real Time Object Recognition using Machine learning

  • Kadhim M
  • Oleiwi B
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Abstract

Healthy people carry out their daily lives normally, but the visually impaired and the blind face difficulties in practicing their daily activities safely because they are ignorant of the organisms surrounding them. Smart systems come as solutions to help this segment of people in a way that enables them to practice their daily activities safely as possible. Blind assistive system using deep learning based You Only Look Once algorithm (YOLO) and Open CV library for detecting and recognizing objects in images and video streams quickly. This work implemented using python. The results gave a satisfactory performance in detecting and recognizing objects in the environment. The results obtained are the identification of the objects that the Yolo algorithm was trained on, where the persons, chairs, oven, pizza, mugs, bags, seats, etc. were identified.

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Kadhim, M., & Oleiwi, B. (2022). Blind Assistive System based on Real Time Object Recognition using Machine learning. Engineering and Technology Journal, 40(1), 159–165. https://doi.org/10.30684/etj.v40i1.1933

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