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This paper proposes a systematic approach to evaluate algorithms for extracting road marking features from images. This specific topic is seldom addressed in the literature while many road marking detection algorithms have been proposed. Most of them can be decomposed into three steps: extracting road marking features, estimating a geometrical marking model, tracking the parameters of the geometrical model along an image sequence. The present work focuses on the first step, i.e. feature extraction. A reference database containing over 100 images of natural road scenes was built with corresponding manually labeled ground truth images (available at http://www.lcpc.fr/en/produits/ride/). This database enables to evaluate and compare extractors in a systematic way. Different road marking feature extraction algorithm representing different classes of techniques are evaluated: thresholding, gradient analysis, and convolution. As a result of this analysis, recommendations are given on which extractor to choose according to a specific application.
Veit et al. (Wed,) studied this question.