University of Oulu

Pham, G. N., Tran, T. V., Nguyen, H. T., Nguyen, P. H., Le, B. N., Risk detection solution on road based on image processing and deep learning, International Journal of Scientific & Technology Research, ISSN: 2277-8616, Vol. 9:3, p. 5714-5718

Risk detection solution on road based on image processing and deep learning

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Author: Pham, Giao N.1; Tran, Thang V.2; Nguyen, Hai T.3;
Organizations: 1Dept. of Computing Fundamentals, FPT University, Hanoi, Vietnam
2Institute of Engineering, Ho Chi Minh University of Technology, Ho Chi Minh city, Vietnam
3Institute of Engineering, Ho Chi Minh City University of Technology, Ho Chi Minh city, Vietnam
4Center of Machine Vision and Signal Analysis, University of Oulu, Finland
5Aeronautical Electronics & Telecommunications Faculty, Viet Nam Aviation Academy
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020071047220
Language: English
Published: Amazedia Solutions, 2020
Publish Date: 2020-07-10
Description:

Abstract

Safety for pupils on the way to school is always the care of their parents. Because of on the way to school pupils can be meet many risks and dangerous issues as accident, violence, kidnapper, and stranger. Thus, their parents always desire to know the status of pupils on the way to school, and they also desire a solution to detect risks on the road and generate warning to pupils. In this paper, we would like to propose a risk detection solution on the road for pupils based on object detection, face detection and distance estimation. The proposed solution uses the techniques of image processing and deep learning to detect dangerous objects, human face and estimate the distance from the detected objects to pupil to give necessary warnings. Experimental results on the road verified that the proposed solution works well, and it have been responded to the purpose of risk detection on the road for pupils in the real.

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Series: International journal of scientific & technological research
ISSN: 2277-8616
ISSN-E: 2277-8616
Volume: 9
Issue: 3
Pages: 5714 - 5718
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This work is supported by the FPT University, Hanoi, Vietnam; Ho Chi Minh University of Technology, Ho Chi Minh city, Vietnam; and Aeronautical Electronics & Telecommunications Faculty, Viet Nam Aviation Academy.
Copyright information: © IJSTR 2020.