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Fallah, A., Soliemani, A., Khosravi, H.. (1399). Real-time Lane Detection Based on Image Edge Feature and Hough Transform. فناوری آموزش, 9(2), 193-202. doi: 10.22061/jecei.2021.7659.418
A. Fallah; A. Soliemani; H. Khosravi. "Real-time Lane Detection Based on Image Edge Feature and Hough Transform". فناوری آموزش, 9, 2, 1399, 193-202. doi: 10.22061/jecei.2021.7659.418
Fallah, A., Soliemani, A., Khosravi, H.. (1399). 'Real-time Lane Detection Based on Image Edge Feature and Hough Transform', فناوری آموزش, 9(2), pp. 193-202. doi: 10.22061/jecei.2021.7659.418
Fallah, A., Soliemani, A., Khosravi, H.. Real-time Lane Detection Based on Image Edge Feature and Hough Transform. فناوری آموزش, 1399; 9(2): 193-202. doi: 10.22061/jecei.2021.7659.418

Real-time Lane Detection Based on Image Edge Feature and Hough Transform

Journal of Electrical and Computer Engineering Innovations (JECEI)
مقاله 7، دوره 9، شماره 2، مهر 2021، صفحه 193-202    اصل مقاله (992.07 K)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22061/jecei.2021.7659.418
نویسندگان
A. Fallah* ؛ A. Soliemani؛ H. Khosravi
Department of Electronics, Faculty of Electrical Engineering, Shahrood University of Technology, Shahrood, Iran
تاریخ دریافت: 13 شهریور 1399،  تاریخ بازنگری: 22 دی 1399،  تاریخ پذیرش: 16 اسفند 1399 
چکیده
Background and Objectives: Lane detection systems are an important part of safe and secure driving by alerting the driver in the event of deviations from the main lane. Lane detection can also save the lifes of car occupants if they deviate from the road due to driver distraction.
Methods: In this paper, a real-time and illumination invariant lane detection method on high-speed video images is presented in three steps. In the first step, the necessary preprocessing including noise removal, image conversion from RGB colour to grey and the binarizing input image is done. Then, a polygon area as the region of interest is chosen in front of the vehicle to increase the processing speed. Finally, edges of the image in the region of interest are obtained with edge detection algorithm and then lanes on both sides of the vehicle are identified by using the Hough transform.
Results: The implementation of the proposed method was performed on the IROADS database. The proposed method works well under different daylight conditions, such as sunny, snowy or rainy days and inside the tunnels. Implementation results show that the proposed algorithm has an average processing time of 28 milliseconds per frame and detection accuracy of 96.78%.
Conclusion: In this paper a straightforward method to identify road lines using the edge feature is described on high-speed video images.
 

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Copyrights
©2021 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.
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کلیدواژه‌ها
Lane Detection؛ Real-time Processing؛ Region of Interest؛ Hough Transform؛ Edge Detection
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