Real Time Drowsy Driver Detection Using Image Processing on Python
Drowsy driving is one of the most common causes of road accidents. Human usually become drowsy when tired and it is dangerous especially during driving on the road. Drowsiness can induce microsleep which can cause a significant decline in driving performance and thus would increase the chance of acc...
Published in: | ICCSCE 2022 - Proceedings: 2022 12th IEEE International Conference on Control System, Computing and Engineering |
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Institute of Electrical and Electronics Engineers Inc.
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2-s2.0-85142440725 Faidhi Daud M.A.; Ismail A.P.; Tahir N.M.; Daud K.; Kasim N.M.; Mohamad F.A. Real Time Drowsy Driver Detection Using Image Processing on Python 2022 ICCSCE 2022 - Proceedings: 2022 12th IEEE International Conference on Control System, Computing and Engineering 10.1109/ICCSCE54767.2022.9935627 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142440725&doi=10.1109%2fICCSCE54767.2022.9935627&partnerID=40&md5=4af6001df795f000fa1f1da31a7cf90b Drowsy driving is one of the most common causes of road accidents. Human usually become drowsy when tired and it is dangerous especially during driving on the road. Drowsiness can induce microsleep which can cause a significant decline in driving performance and thus would increase the chance of accidents. Hence, this real time drowsy driver detection is developed that to help minimize the chance of road accidents occurrence when the driver become drowsy. In this proposed method, the drowsy driver can be detected and alerted without using any intrusive instruments that could distract the driver. This drowsy detection is done using real time input image of the driver using a camera and image processing using Python. Next, drowsiness sign can be detected from the facial expression of the driver through the percentage of eyes opened and the frequent yawning. From the facial expression, the calculation of the eye closure known as eye aspect ratio (EAR) and the wideness of mouth opening known as mouth aspect ratio (MAR) can be made. Finally, using the value obtained, the system can determine whether the driver is alert or drowsy. © 2022 IEEE. Institute of Electrical and Electronics Engineers Inc. English Conference paper |
author |
Faidhi Daud M.A.; Ismail A.P.; Tahir N.M.; Daud K.; Kasim N.M.; Mohamad F.A. |
spellingShingle |
Faidhi Daud M.A.; Ismail A.P.; Tahir N.M.; Daud K.; Kasim N.M.; Mohamad F.A. Real Time Drowsy Driver Detection Using Image Processing on Python |
author_facet |
Faidhi Daud M.A.; Ismail A.P.; Tahir N.M.; Daud K.; Kasim N.M.; Mohamad F.A. |
author_sort |
Faidhi Daud M.A.; Ismail A.P.; Tahir N.M.; Daud K.; Kasim N.M.; Mohamad F.A. |
title |
Real Time Drowsy Driver Detection Using Image Processing on Python |
title_short |
Real Time Drowsy Driver Detection Using Image Processing on Python |
title_full |
Real Time Drowsy Driver Detection Using Image Processing on Python |
title_fullStr |
Real Time Drowsy Driver Detection Using Image Processing on Python |
title_full_unstemmed |
Real Time Drowsy Driver Detection Using Image Processing on Python |
title_sort |
Real Time Drowsy Driver Detection Using Image Processing on Python |
publishDate |
2022 |
container_title |
ICCSCE 2022 - Proceedings: 2022 12th IEEE International Conference on Control System, Computing and Engineering |
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container_issue |
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doi_str_mv |
10.1109/ICCSCE54767.2022.9935627 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142440725&doi=10.1109%2fICCSCE54767.2022.9935627&partnerID=40&md5=4af6001df795f000fa1f1da31a7cf90b |
description |
Drowsy driving is one of the most common causes of road accidents. Human usually become drowsy when tired and it is dangerous especially during driving on the road. Drowsiness can induce microsleep which can cause a significant decline in driving performance and thus would increase the chance of accidents. Hence, this real time drowsy driver detection is developed that to help minimize the chance of road accidents occurrence when the driver become drowsy. In this proposed method, the drowsy driver can be detected and alerted without using any intrusive instruments that could distract the driver. This drowsy detection is done using real time input image of the driver using a camera and image processing using Python. Next, drowsiness sign can be detected from the facial expression of the driver through the percentage of eyes opened and the frequent yawning. From the facial expression, the calculation of the eye closure known as eye aspect ratio (EAR) and the wideness of mouth opening known as mouth aspect ratio (MAR) can be made. Finally, using the value obtained, the system can determine whether the driver is alert or drowsy. © 2022 IEEE. |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
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English |
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Conference paper |
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scopus |
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Scopus |
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1809678025837510656 |