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Proceedings Paper

A vision-based detection algorithm for unmarked road
Author(s): Qingji Gao; Moli Sun; Xiayan Si; Guoqing Yang
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Paper Abstract

A new detection method for unstructured road based on robot's vision is proposed to improve the effectiveness of road detection in complex environment. In this article, the OTSU, an auto-adapted threshold searching algorithm, is mainly used to classify the road images. Meanwhile, to solve the problems of misclassification in complex environment, the OTSU will be used the second time to subdivide. And multiple scene templates are built combining road referring window (RRW). Then, multi-dimensional features are chosen for region reorganizing according to those templates to obtain the optimal classification. At last, the classifying results are merged by referring RRW to extract the final road region accurately. This algorithm shows good self-adaptive ability and only needs little priori knowledge. It is also robust against noises, shadows and illumination variations and shows good real-time performance. It has been tested on real robot and performed well in real road environment.

Paper Details

Date Published: 28 November 2007
PDF: 9 pages
Proc. SPIE 6833, Electronic Imaging and Multimedia Technology V, 68330T (28 November 2007); doi: 10.1117/12.756423
Show Author Affiliations
Qingji Gao, Nanjing Univ. of Aeronautics and Astronautics (China)
Civil Aviation Univ. of China (China)
Moli Sun, Northeast Dianli Univ. (China)
Xiayan Si, Northeast Dianli Univ. (China)
Guoqing Yang, Nanjing Univ. of Aeronautics and Astronautics (China)

Published in SPIE Proceedings Vol. 6833:
Electronic Imaging and Multimedia Technology V
Liwei Zhou; Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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