반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

한국반도체디스플레이기술학회 (The Korean Society Of Semiconductor & Display Technology)
권호 표지

연결 성분 분석과 크기 정규화를 이용한 도로 노면 표시와 숫자 인식

Recognition of Road Surface Marks and Numbers Using Connected Component Analysis and Size Normalization

  • 정민철 (상명대학교 전자공학과)
  • Jung, Min Chul (Dept. of Electronic Engineering, Sangmyung University)
  • 투고 : 2022.01.26
  • 심사 : 2022.02.28
  • 발행 : 2022.03.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper proposes a new method for the recognition of road surface marks and numbers. The proposed method designates a region of interest on the road surface without first detecting a lane. The road surface markings are extracted by location and size using a connection component analysis. Distortion due to the perspective effect is minimized by normalizing the size of the road markings. The road surface marking of the connected component is recognized by matching it with the stored road marking templates. 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 recognition of road surface marks and numbers.

키워드

과제정보

본 연구는 2020년도 상명대학교 교내연구비를 지원받아 수행하였습니다.

참고문헌

  1. Stefan Vacek, Constantin Schimmel, Rudiger Dillmann, "Road-marking Analysis for Autonomous Vehicle Guidance," Conference: Proceedings of the 3rd European Conference on Mobile Robots, EMCR, pp. 19-21, (2007).
  2. G. Maier, S. Pangerl, A. Schindler, "Real-time detection and classification of arrow markings using curve-based prototype fitting," 2011 IEEE Intelligent Vehicles Symposium (IV), pp. 442-447, (2011).
  3. Radu Danescu, Sergiu Nedevschi, "Detection and classification of painted road objects for intersection assistance applications," 13th International IEEE Conference on Intelligent Transportation Systems, pp. 19-22, (2010).
  4. Minchul Jung, "Infrared Image Enhancement Using A Histogram Partition Stretching and Shrinking Method," Journal of The Korean Society of Semiconductor & Display Technology, Vol. 14, No. 4, pp. 50-55, (2015).
  5. Yong Jin Joo, Chang Hahk Hahm, "A Study on Automatic Detection of Speed Bump by using Mathematical Morphology Image Filters while Driving," Journal of Korean Society for Geospatial Information Science, Vol. 21, No. 3, pp. 55-62, (2013).
  6. H. Samet and M. Tamminen, "Efficient component labeling of images of arbitrary dimension represented by linear bintrees," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 10, Is. 4, pp. 579-586, (1988). https://doi.org/10.1109/34.3918
  7. M. Dillencourt, H. Samet and M. Tamminen, "A general approach to connected-component labeling for arbitrary image representations," Journal of the Association for Computing Machinery, Vol. 39, Is. 2, pp. 253-280, (1992). https://doi.org/10.1145/128749.128750
  8. M. Nadler and E. Smith, "Pattern Recognition Engineering," John Wiley & Sons Inc., pp. 155-159, 291-294, (1993).