VEHICLE POSITIONING BY DEEP LEARNING BASED LANE DETECTION AND DROWSINESS ATTENTION ALERT BY EYE ASPECT RATIO FOR DRIVER SAFETY

Geetha Guttikonda Assistant Professor, Department of IT, Velagapudi Ramakrishna Siddhartha Engineering College
Paruchuri Ramya Assistant Professor, Department of IT, Velagapudi Ramakrishna Siddhartha Engineering College
K.Madhavi Assistant Professor, Department of IT, Velagapudi Ramakrishna Siddhartha Engineering College

Abstract

The challenging task for autonomous driving is Lane Detection. The multi feature extraction has been the real problem for computer vision and machine learning tasks. Canny Library Functions are used from OPENCV through which edge detection is attained. Essentially Lane detection has become a major important problem for identification of lanes along with object detection. Hough Transform technique is used for the straight lines identification or detection of Lanes. Detection of drowsiness is also identified based on the eye-aspect ratio. The proposed work differentiates the driver sleepiness and eye blink so as to prevent the risk of accidents. Canny edge detection using Deep Learning is used to localize the area of the road. By such observation, the safety of the persons in the vehicle can be implemented in normal cars also

 

 

 

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References



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