Real Time Object Detection System
T S Hari baskaran1, Bhuvaneswari Balachander2

1T S Hari baskaran, UG scholarunder the stream of Electronics and Communication Engineering. Saveetha School of Engineering, SIMATS, Ponnamalle, Chennai.
2Bhuvaneswari Balachander , Assistant Professor for the department of ECE, Saveetha School of Engineering, SIMATS, Ponnamalle, Chennai.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 59-62 | Volume-8 Issue-6, August 2019. | Retrieval Number: E7440068519/2019©BEIESP | DOI: 10.35940/ijeat.E7440.088619
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (

Abstract: 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 can distinguish the lost articles with the assistance of our proposed framework utilizing Image handling procedures. That additionally ready to support the individual depend to  the face recognized and confine or personal the passage of obscure people. The current framework distinguied she the lost articles with the assistance of GPS. Yet, the use off aceac knowledge ment 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.
Keywords: Raspberry PI, GPS, Visually impaired, Image Segmentation, Convolutional neural networks, face recognition.