@inproceedings{a1ac7020e08e4eff82e98e7a01b79d9d,
title = "Automatic road segmentation of traffic images",
abstract = "Automatic road segmentation plays an important role in many vision-based traffic applications. It provides a priori information for preventing the interferences of irrelevant objects, activities, and events that take place outside road areas. The proposed road segmentation method consists of four major steps: background-shadow model generation and updating, moving object detection and tracking, background pasting, and road location. The full road surface is finally recovered from the preliminary one using a progressive fuzzytheoretic shadowed sets technique. A large number of video sequences of traffic scenes under various conditions have been employed to demonstrate the feasibility of the proposed road segmentation method.",
keywords = "Background-shadow model, Fuzzy decision, Shadow set",
author = "Fang, \{Chiung Yao\} and Chou, \{Han Ping\} and Wang, \{Jung Ming\} and Chen, \{Sei Wang\}",
year = "2015",
doi = "10.5220/0005321904690477",
language = "English",
series = "VISAPP 2015 - 10th International Conference on Computer Vision Theory and Applications; VISIGRAPP, Proceedings",
publisher = "SciTePress",
pages = "469--477",
editor = "Jose Braz and Sebastiano Battiato and Francisco Imai",
booktitle = "Proceedings of the 10th International Conference on Computer Vision Theory and Applications, VISAPP 2015",
note = "10th International Conference on Computer Vision Theory and Applications, VISAPP 2015 ; Conference date: 11-03-2015 Through 14-03-2015",
}