Road Triangle Detection for Non-Road Area Elimination Using Lane Detection and Image Multiplication

Authors

  • Nur Shazwani A. Faculty of Electronic and Computer Engineering (FKEKK) Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Melaka, Malaysia.
  • M. M. Ibrahim Faculty of Electronic and Computer Engineering (FKEKK) Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Melaka, Malaysia.
  • N. M. Ali Faculty of Electrical Engineering (FKE) Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Melaka, Malaysia.
  • S. A. Radzi Faculty of Electronic and Computer Engineering (FKEKK) Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Melaka, Malaysia.
  • A. M. Darsono Faculty of Electronic and Computer Engineering (FKEKK) Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Melaka, Malaysia.
  • W. Y. Chiew Faculty of Electronic and Computer Engineering (FKEKK) Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Melaka, Malaysia.

Keywords:

Background Removal, Image Processing, Lane Detection, Road Triangle, Vanishing Point,

Abstract

The background has become the key issue in maintaining the accuracy of final analysis for object detection in the development of an image processing algorithm. Therefore, this paper focuses on intelligent transport system (ITS), in which some of the background characteristics such as trees, road divider, and buildings interfere in the detection system algorithm. Therefore, this paper presents an algorithm that can remove the unwanted background, outside the road area boundaries for dynamic video footage. Using the onboard camera to capture the road traffic, the background is always moving in motion together with the foreground; therefore, a region of interest that focuses only on the road region needs to be established. The algorithm consists of three main components: lane detection, vanishing point and image multiplication. From the three components, other methods are applied, namely Hough transform, line intersection, image masking and image multiplication, which are combined together to create the background subtraction system. In the final analysis, the test results under various road conditions show a good detection rate and background removal.

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Published

2017-09-01

How to Cite

A., N. S., M. Ibrahim, M., M. Ali, N., A. Radzi, S., Darsono, A. M., & Chiew, W. Y. (2017). Road Triangle Detection for Non-Road Area Elimination Using Lane Detection and Image Multiplication. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-8), 73–77. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2631

Issue

Vol. 9 No. 2-8: Towards Creative and Innovative Technologies for Humankind II

Section

Articles

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