Open AccessRoad Lane Marking Detection with Deep Learning
Author(s) -
Siddharth Manu
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.37463
Subject(s) - computer science , artificial intelligence , convolutional neural network , segmentation , computer vision , deep learning , advanced driver assistance systems , edge detection , enhanced data rates for gsm evolution , pattern recognition (psychology) , image (mathematics) , image processing
Road Lane detection is an important factor for Advanced Driver Assistant System (ADAS). In this paper, we propose a lane detection technology using deep convolutional neural network to extract lane marking features. Many conventional approaches detect the lane using the information of edge, color, intensity and shape. In addition, lane detection can be viewed as an image segmentation problem. However, most methods are sensitive to weather condition and noises; and thus, many traditional lane detection systems fail when the external environment has significant variation.