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In response to the alarming increase in road accidents attributed to driver inattention, recent advancements in road safety technology have become imperative. Addressing this concern, Lane Detection Systems have emerged as a pivotal component in technologically advanced transportation systems. These systems function by identifying lane boundaries on the road and promptly alerting the driver if there is deviation from correct lane markings. However, achieving robust lane detection poses challenges due to diverse road conditions encountered during driving, including night time and day time scenarios. This research focuses on a Lane Detection System that employs a front-facing camera to capture the road view and identify lane boundaries. The proposed method involves dividing the video image. This research presents the study explores various techniques for detecting lane markings, series of sub-images, extracting image features for each segment, and utilizing these features to recognize lanes on the road, acknowledging the complexity introduced by different driving conditions.
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Kushwaha et al. (2024) studied this question.
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