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تشخیص خواب آلودگی راننده با استفاده از تلفیق روش پردازش تصویر ویولا-جونز و آشکارسازی لندمارک های تصویر | ||
| نشریه مهندسی عمران امیرکبیر | ||
| دوره 57، شماره 3، 1404، صفحه 489-506 اصل مقاله (1.36 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/ceej.2025.23159.8122 | ||
| نویسندگان | ||
| ساناز اسکندری1؛ امیر مسعود رحیمی* 1؛ احسان رمضانی خوانساری2 | ||
| 1گروه عمران، دانشکده مهندسی، دانشگاه زنجان، زنجان، ایران | ||
| 2دانشکده فنی و مهندسی، دانشگاه بین المللی امام خمینی، قزوین، ایران | ||
| چکیده | ||
| خستگی یکی از دلایل اصلی تصادفات رانندگی است که سالانه منجر به مرگ و میر بسیاری از مردم در جادهها میشود. روشهای متعددی برای تشخیص میزان خستگی ایجاد شده است. یکی از روشها، تشخیص خستگی هوشمند و استفاده از پارامترهای مختلف (ابزارها) در زمان طولانی و با استفاده از سابقه رانندگی است. این مزیت منجر به تشخیص خستگی در مراحل اولیه و فعالسازی زنگ هشدار قبل از وقوع تصادف رانندگی میشود. هدف این تحقیق تشخیص خوابآلودگی از روی حالت چهره میباشد. با استخراج و ردیابی نقاط کلیدی میتوان حالت چهره شخص مانند حالت عادی یا خوابآلوده را تشخیص داد. در این مقاله روش جدید برای تشخیص خوابآلودگی از روی فریمهای ویدئویی با استفاده از پایگاه داده YawDD میباشد. نحوه عملکرد سیستم پیشنهادی براساس ردیابی لندمارکهای چهره استخراج شده از فریمهای ویدئویی است. در ابتدا موقعیت اولیه چهره با استفاده از الگوریتم ویولاجونز مشخص میشود، سپس نقاط کلیدی توسط الگوریتم سیفت استخراج میشوند. این روش قادر است با دقت خوبی عملیات تشخیص خوابآلودگی راننده را انجام دهد. روش پیشنهادی قادر است با دقت خوبی عملیات تشخیص خوابآلودگی راننده را انجام دهد. از دیگر مزایای روش پیشنهادی میتوان به اجرای بلادرنگ 47 فریم بر ثانیه و دقت 94 درصد و خطای 6% بر روی پایگاه داده YawDD اشاره کرد. | ||
| کلیدواژهها | ||
| خستگی؛ ردیابی چهره؛ ویولا جونز؛ خوابآلودگی؛ پردازش تصویر | ||
| موضوعات | ||
| پردازش تصویر؛ راه و ترابری و حمل و نقل - ترابری هوشمند | ||
| عنوان مقاله [English] | ||
| Detecting Driver Drowsiness by Combining Viola-Jones Image Processing Method and Image Landmarks Detection | ||
| نویسندگان [English] | ||
| Sanaz Eskandari1؛ Amir Masoud Rahimi1؛ Ehsan Ramezani Khansari2 | ||
| 1Department of Civil Engineering, Faculty of Engineering, University of Zanjan, Zanjan, Iran | ||
| 2Department of Transportation, Faculty of Engineering, Imam Khomeini International University, Qazvin, Iran | ||
| چکیده [English] | ||
| Fatigue is one of the main causes of traffic crashes which leads to the death of many people on the roads every year. Several methods have been developed to detect the level of fatigue, one of which is intelligent fatigue detection based on driving history. This advantage leads to the detection of fatigue in the early stages and notifying before the crash. In this paper, a new method is applied to detect drowsiness from video frames using the YawDD database. The operation of the proposed system is based on the tracking of facial landmarks. The purpose of this paper is to detect drowsiness from facial expressions. By extracting and tracking key points, facial expressions such as normal or sleepy can be detected. First, the initial position of the face is determined and then the key points are extracted using Viola-Jones and SIFT algorithms, respectively. The results showed that the proposed method is capable of detecting the driver's drowsiness with good accuracy. The proposed method executed 47 frames per second in real-time with an accuracy of 94% and an error rate of 6%. | ||
| کلیدواژهها [English] | ||
| Car Accidents, Fatigue, Viola-Jones, Drowsiness, Facial Tracking | ||
| مراجع | ||
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