Comparison of Machine Vision Algorithms used by Autonomous Driving Robots to Recognize Road Signs in Underground Mines

Heonmoo Kim and Yosoon Choi

doi:10.32390/ksmer.2021.58.6.559

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2021 Vol.58, Issue 6 Preview Page Next Page

Research Paper

Comparison of Machine Vision Algorithms used by Autonomous Driving Robots to Recognize Road Signs in Underground Mines 지하광산용 자율주행 로봇의 도로 표지판 인지를 위한 머신비전 알고리즘 비교

31 December 2021. pp. 559-567

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Abstract

본 연구에서는 자율주행 로봇이 지하광산에서 도로 표지판을 인지하기 위해 사용될 수 있는 4종의 머신비전 알고리즘(컬러 패턴 매칭, 기하 매칭, 패턴 매칭, 형상 매칭)을 비교하였다. 실내실험을 통해 자율주행 로봇과 도로 표지판 사이의 거리와 각도 조건을 달리하면서 각각의 알고리즘의 표지판 인지 정확도를 평가하였다. 기하 매칭 알고리즘이 가장 높은 표지판 인지 정확도를 나타냈다. 추가적으로 조명의 여부와 상징(symbol) 변화에 따라 기하 매칭 알고리즘 도로 표지판 인지 정확도를 평가하였다. 기하 매칭 알고리즘은 조명 조건과 도로 표지판의 상징이 달라질 때도 안정적으로 작동하였다.

키워드

자율주행 로봇

머신비전

도로 표지판 인지

지하광산

This study compared four types of machine vision algorithms (color pattern matching, geometric matching, pattern matching, shape matching) used by autonomous driving robots to recognize road signs in underground mines. Through an indoor experiment, the accuracy of sign recognition using each algorithm was evaluated while varying the distance and angle between the autonomous driving robot and the road sign. Consequently, the geometric matching algorithm showed the highest accuracy of sign recognition. Additionally, the accuracy of sign recognition obtained using this algorithm was evaluated according to the presence or absence of lighting and symbol changes. This algorithm could reliably recognize road signs even under different lighting conditions and symbols.

Keywords

Autonomous driving robot

Machine vision

Road sign recognition

Underground mine

References

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Information

Publisher :The Korean Society of Mineral and Energy Resources Engineers
Publisher(Ko) :한국자원공학회
Journal Title :Journal of the Korean Society of Mineral and Energy Resources Engineers
Journal Title(Ko) :한국자원공학회지
Volume : 58
No :6
Pages :559-567
Received Date :2021. 11. 22
Revised Date :2021. 12. 22
Accepted Date : 2021. 12. 27
DOI :https://doi.org/10.32390/ksmer.2021.58.6.559

Journal of the Korean Society of Mineral and Energy Resources Engineers ISSN:2288-0291(Print) 2288-2790(Online) 한국자원공학회지

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