Drowsy Driver Detection Based on Eye by Using Digital Image Processing
نویسندگان
چکیده
منابع مشابه
Drowsy Driver Identification Using Eye Blink detection
As field of signal processing is widening in various security and surveillance applications, motivated the interest for implementing better application with less complications. A non-intrusive machine vision based concepts is used to simulate Drowsiness Detection System. The system is consisting of web camera which placed in a way that it records driver’s head movements in order to detect drows...
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Due to the increasing growth in population, the occurrence of vehicle accidents has also seen an increase. A detailed analysis shows that, around half million accidents occur in a year, in India alone. Drowsiness and sleeping while driving are now identified as one of the reasons behind fatal crashes and highway accidents caused by drivers. Various drowsiness detection techniques researched are...
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Drivers who do not take regular breaks when driving long distances run a high risk of becoming drowsy a state which they often fail to recognize early enough according to the experts. Studies show that around one quarter of all serious motorway accidents are attributable to sleepy drivers in need of a rest, meaning that drowsiness causes more road accidents than drink-driving. Attention assist ...
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Today most accidents are caused by drivers’ fatigue, drowsiness and losing attention on the road ahead. In this paper, a system is introduced, using RGB-D cameras to automatically identify drowsiness and give warning. In this system two important modules have been utilized simultaneously to identify the state of driver’s mouth and eyes for detecting drowsiness. At first, using the depth informa...
متن کاملDrowsy Detection On Eye Blink Duration Using Algorithm
this paper presents an automatic drowsy driver monitoring and accident prevention system that is based on monitoring the changes in the eye blink duration. Our proposed method detects the drowsiness in eyes using the proposed mean sift algorithm. Our new method detects eye blinks via a standard webcam in real-time YUY2_640x480 resolution. Experimental results in the eyeblink database showed tha...
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ژورنال
عنوان ژورنال: SKIT Research Journal
سال: 2020
ISSN: 2454-9673,2278-2508
DOI: 10.47904/ijskit.10.2.2020.34-40