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Title: Image Processing Application to Detect Driver Drowsiness using Raspberry PI kit
Other Titles: Ứng dụng xử lý ảnh phát hiện tài xế ngủ gật sử dụng kit Raspberry
Authors: Tran, Thanh
Nguyen, Van Chuc
Keywords: Detect Driver Drowsiness
Raspberry PI
Issue Date: Jan-2024
Publisher: Vietnam-Korea University of Information and Communication Technology
Series/Report no.: KLTN;19CE007
Abstract: In this project, we aim to find real-time responsive algorithms, optimal and simple solutions that provide high accuracy and meet practical needs. We simulate simple image processing problems, static image recognition, and direct recognition through the camera using Python programming. We also develop accurate eye state tracking in realtime on the Raspberry Pi 4 Kit. Face detection is performed using the AdaBoost classifier method based on Haar-like features. Eye recognition is achieved by marking the facial features using the Facial Landmarks algorithm, and then calculating the Euclidean distance between the two eye folds to detect the eye state and identify drowsiness.
Description: Graduation thesis of Computer Engineering Technology; 2019 - 2024.
Appears in Collections:ĐH-Công nghệ kỹ thuật máy tính (Computer Engineering)

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