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مقاله A New System for Driver Drowsiness and Distraction Detection word دارای 5 صفحه می باشد و دارای تنظیمات در microsoft word می باشد و آماده پرینت یا چاپ است

فایل ورد مقاله A New System for Driver Drowsiness and Distraction Detection word کاملا فرمت بندی و تنظیم شده در استاندارد دانشگاه و مراکز دولتی می باشد.

این پروژه توسط مرکز مرکز پروژه های دانشجویی آماده و تنظیم شده است

توجه : در صورت  مشاهده  بهم ریختگی احتمالی در متون زیر ،دلیل ان کپی کردن این مطالب از داخل فایل ورد می باشد و در فایل اصلی مقاله A New System for Driver Drowsiness and Distraction Detection word ،به هیچ وجه بهم ریختگی وجود ندارد

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بخشی از متن مقاله A New System for Driver Drowsiness and Distraction Detection word :

سال انتشار: 1391
محل انتشار: بیستمین کنفرانس مهندسی برق ایران
تعداد صفحات: 5
چکیده:

Drowsiness especially in long distance journeys is a key factor in traffic accidents. In this paper a new module for automatic driver drowsiness detection based on visual informationand Artificial Intelligence is presented. The aim of this system is to locate, track and analyze both the driver’s face and eyes tocompute a drowsiness index to prevent accidents. Both face and eye detection is performed by Haar-like features and AdaBoost classifiers. In order to achieve better accuracy in face tracking,we propose a new method which is combination of detection and object tracking. Proposed face tracking method, also hascapability to self correction. After eye region is found, Local Binary Pattern (LBP) is employed to extract eye characteristics.Using these features, an SVM classifier was trained to perform eye state analysis. To evaluate the effectiveness of proposed method, a drowsy person was pictured, while his EEG signalswere taken. In this video we were able to track face by an accuracy of 100% and detecting eye blink by accuracy of 98.4%.Also we can calculate face orientation and tilt using eye position which is valuable knowledge about driver concentration. Finally,we can make a decision about drowsiness and distraction of the driver. Experimental results show high accuracy in each sectionwhich makes this system reliable for driver drowsiness detection

 

 

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