DocumentCode :
182915
Title :
Unstructured road detection based on fuzzy clustering arithmetic
Author :
Xiao Liu ; KeKe Shang ; Jie Liu ; Chun Yu Zhou
Author_Institution :
Coll. of Sci., Tianjin Polytech. Univ., Tianjin, China
fYear :
2014
fDate :
19-21 Aug. 2014
Firstpage :
114
Lastpage :
118
Abstract :
The unstructured road detection plays a key role in an autonomous vehicle navigation system. However, the unstructured road images often contain shadows and are easily affected by ambient light, resulting to an inaccuracy with road detection. A robust road detection technique is required. In this paper, we adopted an improved fuzzy c-means(FCM) clustering algorithm to address these issues. The new technique considered the neighborhood impact factor when calculating distances between the cluster center and a pixel. Our experimental results show that the improved FCM have better outcomes.
Keywords :
fuzzy set theory; mobile robots; object detection; path planning; pattern clustering; remotely operated vehicles; ambient light; autonomous vehicle navigation system; fuzzy clustering arithmetics; improved FCM clustering algorithm; improved fuzzy c-means clustering algorithm; robust road detection technique; unstructured road detection; unstructured road images; Clustering algorithms; Color; Feature extraction; Image color analysis; Image segmentation; Roads; Robustness; HSV Color Space; cluster; fuzzy c-means; unstructured road detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2014 11th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5147-5
Type :
conf
DOI :
10.1109/FSKD.2014.6980817
Filename :
6980817
Link To Document :
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