Distance measurement for self-driving cars using stereo camera
Self-driving cars reduce human error and can accomplish various missions to help people in different fields.They have become one of the main interests in automotive research and development, both in the industry and academia. However, many challenges are encountered in dealing with distance measurem...
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my.uum.repo.228342017-07-26T08:33:03Z http://repo.uum.edu.my/22834/ Distance measurement for self-driving cars using stereo camera Salman, Yasir Dawood Ku-Mahamud, Ku Ruhana Kamioka, Eiji QA75 Electronic computers. Computer science Self-driving cars reduce human error and can accomplish various missions to help people in different fields.They have become one of the main interests in automotive research and development, both in the industry and academia. However, many challenges are encountered in dealing with distance measurement and cost, both in equipment and technique.The use of stereo camera to measure the distance of an object is convenient and popular for obstacle avoidance and navigation of autonomous vehicles.The calculation of distance considers angular distance, distance between cameras, and the pixel of the image.This study proposes a method that measures object distance based on trigonometry, that is, facing the self-driving car using image processing and stereo vision with high accuracy, low cost, and computational speed.The method achieves a high distance measuring accuracy of up to 20 m. It can be implemented in real time computing systems and can determine the safe driving distance between obstacles. 2017-04-25 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/22834/1/ICOCI%202017%20235-242.pdf Salman, Yasir Dawood and Ku-Mahamud, Ku Ruhana and Kamioka, Eiji (2017) Distance measurement for self-driving cars using stereo camera. In: 6th International Conference on Computing & Informatics (ICOCI2017), 25 - 27 April 2017, Kuala Lumpur. http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap04e/PID105-235-242e.pdf |
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QA75 Electronic computers. Computer science Salman, Yasir Dawood Ku-Mahamud, Ku Ruhana Kamioka, Eiji Distance measurement for self-driving cars using stereo camera |
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Self-driving cars reduce human error and can accomplish various missions to help people in different fields.They have become one of the main interests in automotive research and development, both in the industry and academia. However, many challenges are encountered in dealing with distance measurement and cost, both in equipment and technique.The use of stereo camera to measure the distance of an object is convenient and popular for obstacle avoidance and navigation of autonomous vehicles.The calculation of distance considers angular distance, distance between cameras, and the pixel of the image.This study proposes a method that measures object distance based on trigonometry, that is, facing the self-driving car using image processing and stereo vision with high accuracy, low cost, and computational speed.The method achieves a high distance measuring accuracy of up to 20 m. It can be implemented in real time computing systems and can determine the safe driving distance
between obstacles. |
format |
Conference or Workshop Item |
author |
Salman, Yasir Dawood Ku-Mahamud, Ku Ruhana Kamioka, Eiji |
author_facet |
Salman, Yasir Dawood Ku-Mahamud, Ku Ruhana Kamioka, Eiji |
author_sort |
Salman, Yasir Dawood |
title |
Distance measurement for self-driving cars using stereo camera |
title_short |
Distance measurement for self-driving cars using stereo camera |
title_full |
Distance measurement for self-driving cars using stereo camera |
title_fullStr |
Distance measurement for self-driving cars using stereo camera |
title_full_unstemmed |
Distance measurement for self-driving cars using stereo camera |
title_sort |
distance measurement for self-driving cars using stereo camera |
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2017 |
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http://repo.uum.edu.my/22834/1/ICOCI%202017%20235-242.pdf http://repo.uum.edu.my/22834/ http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap04e/PID105-235-242e.pdf |
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1644283629736558592 |