Determine distances area of traffic lights using image processing algorithms
Traffic lights recognition and detection considered important step in the advanced driver assistance techniques. The suggested system designed to detect the color and area of the traffic light at different distance. The detection of the traffic color based on designed algorithms to separate colors a...
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Published in | AIP conference proceedings Vol. 2547; no. 1 |
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Main Authors | , , , , |
Format | Journal Article Conference Proceeding |
Language | English |
Published |
Melville
American Institute of Physics
02.12.2022
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Subjects | |
Online Access | Get full text |
ISSN | 0094-243X 1551-7616 |
DOI | 10.1063/5.0113085 |
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Abstract | Traffic lights recognition and detection considered important step in the advanced driver assistance techniques. The suggested system designed to detect the color and area of the traffic light at different distance. The detection of the traffic color based on designed algorithms to separate colors and calculate area of the signals. The Three colors (red, green, and yellow) distinguished by threshold for each color red, blue, green, and grayscale to give accurate results. The distance between the camera (car) and the traffic light is determined by scale factor (SCF) equation. The real dimension of the traffic measured manually and converted to pixel to calculate the area of each color. The area of each light within the traffic estimated by morphology method. Thus, the light traffic and the area is determined, and the distance between the traffic light and car is determined. The results show that the behavior of the area and distance of the traffic with the video frame shows logic data in pixel domain. Moreover, the light separation is accurate 100% according to the suggested algorithm. |
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AbstractList | Traffic lights recognition and detection considered important step in the advanced driver assistance techniques. The suggested system designed to detect the color and area of the traffic light at different distance. The detection of the traffic color based on designed algorithms to separate colors and calculate area of the signals. The Three colors (red, green, and yellow) distinguished by threshold for each color red, blue, green, and grayscale to give accurate results. The distance between the camera (car) and the traffic light is determined by scale factor (SCF) equation. The real dimension of the traffic measured manually and converted to pixel to calculate the area of each color. The area of each light within the traffic estimated by morphology method. Thus, the light traffic and the area is determined, and the distance between the traffic light and car is determined. The results show that the behavior of the area and distance of the traffic with the video frame shows logic data in pixel domain. Moreover, the light separation is accurate 100% according to the suggested algorithm. |
Author | Abbas, Heba Kh Al-Zuky, Ali A. Touma, Teeba A. Mohamad, Haidar J. Saleh, Anwar H. Al |
Author_xml | – sequence: 1 givenname: Teeba A. surname: Touma fullname: Touma, Teeba A. organization: Department of Physics, College of Science for Women, University of Baghdad – sequence: 2 givenname: Heba Kh surname: Abbas fullname: Abbas, Heba Kh organization: Department of Physics, College of Science for Women, University of Baghdad – sequence: 3 givenname: Anwar H. Al surname: Saleh fullname: Saleh, Anwar H. Al organization: Department of computer science, College of Science, Mustansiriyah University – sequence: 4 givenname: Haidar J. surname: Mohamad fullname: Mohamad, Haidar J. organization: Department of physics, College of Science, Mustansiriyah University – sequence: 5 givenname: Ali A. surname: Al-Zuky fullname: Al-Zuky, Ali A. organization: Department of physics, College of Science, Mustansiriyah University |
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Editor | Al-Kaabi, Mohammed Abdulhussain Hashim, Jasim Hanoon Joda, Baker A. Abdulateef, Ahmed Mahmood Mohammed, Adnan Ibrahim Madlool, Thaer Mahdi Abdulmunem, Ashwan A. |
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References | Shi, Zou, Zhang (c7) 2016; 17 Yoneda (c5) 2020; 20 Abbas, Kh (c16) 2019; 571 Ahmed, Ahmad, Khan, Asif (c18) 2020; 8 Kareem, Jabbar (c4) 2018; 44 Heba, Abass Anwar, Al-Saleh, Al-Zuky (c17) 2015; 6 Bouktif, Cheniki, Ouni (c6) 2021; 21 Nioche (c10) 2018; 78 Uhl, Leyk, Chiang, Duan, Knoblock (c13) 2018; 7 Leal, Soares, De Almeida, Chung (c3) 2017; 25 Wang (c15) 2019; 90 Senthilkumaran, Thimmiaraja (c14) 2014; 5 |
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Snippet | Traffic lights recognition and detection considered important step in the advanced driver assistance techniques. The suggested system designed to detect the... |
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SubjectTerms | Algorithms Color Image processing Light Mathematical analysis Object recognition Pixels Traffic signals |
Title | Determine distances area of traffic lights using image processing algorithms |
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