Traffic Signal Detection and Recognition Using a Color Segmentation in a HSI Color Model

HSI 색상 모델에서 색상 분할을 이용한 교통 신호등 검출과 인식

  • Jung, Min Chul (Dept. of Electronic Engineering, Sangmyung University)
  • 정민철 (상명대학교 공과대학 전자공학과)
  • Received : 2022.11.24
  • Accepted : 2022.12.15
  • Published : 2022.12.31

Abstract

This paper proposes a new method of the traffic signal detection and the recognition in an HSI color model. The proposed method firstly converts a ROI image in the RGB model to in the HSI model to segment the color of a traffic signal. Secondly, the segmented colors are dilated by the morphological processing to connect the traffic signal light and the signal light case and finally, it extracts the traffic signal light and the case by the aspect ratio using the connected component analysis. The extracted components show the detection and the recognition of the traffic signal lights. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the detection and the recognition of traffic signals.

Keywords

Acknowledgement

본 연구는 2021년도 상명대학교 교내연구비를 지원받아 수행하였습니다.

References

  1. Junik Jung, Dohwan Noh, "Real time detection and recognition of traffic lights using component subtraction and detection masks," Journal of the Institute of Electronics Engineers of Korea, Vol. 43, No. 2, pp. 172-179, 2006.
  2. Gangho Lee, Minyoung Bang, Kyuwon Lee, "Traffic Light and Speed Sign Recognition by using Hierarchical Application of Color Segmentation and Object Feature Information," Journal of the Korea Information Processing Society, Vol. 17-B, No. 3, pp. 207-214, 2010.
  3. Yongkwon Kim, Kisung Lee, Seong Ik Cho, Jeong Ho Park, Kyoungho Choi, "Real-time Identification of Traffic Light and Road Sign for the Next Generation Video-Based Navigation System," Journal of Korea Spatial Information System, Vol. 10, No. 2, pp. 13-24, 2008.
  4. Uhyoon Jung, Hochul Jung, Hyungjin Yoon, "Traffic Signal and Traffic Sign Recognition System For Understanding of Road Condition," Proceedings of the Spring Conference of the Korean Society of Automotive Engineers, pp. 527-531, 2005.
  5. Gyungsung Yang, Guisang Lee, "The Detection of Signals for Auto Navigation," Proceedings of the Fall Conference of the Institute of Electronics Engineers, Vol. 19, No. 2, pp. 527-531, 1996.
  6. Junghwan Kim, Sunkyu Kim, Taemin Lee, Yongjin Lim, Junhong Lim, "Machine Learning based Traffic Light Detection and Recognition Algorithm using Shape Information," Journal of the Institute of Electrical and Electronics Engineers, Vol. 22, No. 1, pp. 46-52, 2018.
  7. Min-Ki Kim, "Traffic Light Recognition Using a Deep Convolutional Neural Network," Journal of Multimedia Society, Vol. 21, No. 11, pp 1244-1253, 2018.
  8. Yeon Ho Chu, Bok Joo Lee, Young Kyu Choi, "A Video based Traffic Light Recognition System for Intelligent Vehicles," Journal of the Semiconductor & Display Technology, Vol. 14, No. 2, pp. 29-34, 2015.
  9. Minchul Jung, "Traffic Signal Detection and Recognition in an RGB Color Space," Journal of the Semiconductor & Display Technology, Vol. 10, No. 3, pp. 53-59, 2011.
  10. Minchul Jung, "Color Segmentation of Vehicle License Plates in the RGB Color Space Using Color Component Binarization," Journal of the Semiconductor & Display Technology, Vol. 13, No. 4, pp. 49-54, 2014.
  11. George H. Joblove and Donald Greenberg, "Color spaces for computer graphics," Computer Graphics, Vol. 12, Issue 3, pp. 20-25, 1978. https://doi.org/10.1145/965139.807362
  12. Jaehoon Cho, Sangho Lee, Youngseop Kim, "Image Retrieval Method Using Color Descriptor," Journal of the Semiconductor & Display Technology, Vol. 7, No. 2, pp. 69-76, 2008.
  13. N. Otsu, "A Threshold Selection Method from Gray Level Histograms," IEEE Transactions on Systems, Man, and Cybernetics, Vol. SMC-9, No. 1, pp. 62-66, 1979. https://doi.org/10.1109/TSMC.1979.4310076
  14. Traffic Signal Installation and Management Manual (Traffic 2-3), National Police Agency, 2005.