|Table of Contents|

Unsupervised Road Scene Segmentation Method

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2012年02期
Page:
232-237
Research Field:
Publishing date:

Info

Title:
Unsupervised Road Scene Segmentation Method
Author(s):
ZHANG Hao-fengYE Qiao-linZHAO Chun-xiaYANG Jing-yu
School of Computer Science and Technology,NUST,Nanjing 210094,China
Keywords:
road scene segmentation XYZ color space Gabor texture K-means clustering graph cut
PACS:
TP391.41
DOI:
-
Abstract:
To solve the problems that lots of training samples are needed in the road scene segmentation and the changes of different roads cause the segmentation error easily,this paper proposes an unsupervised road scene segmentation method.First,K-means clustering method is applied to the first image for its initial segmentation;Second,graph cut optimization algorithm is used to minimize the total image energy to get the optimal segmentation.With the computed class centers of the segmented image,the next image is also optimized by graph cut.Experimental results show that this method can segment the road scene quickly without quantities of training samples,and can keep efficient in changing of different road types.

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Last Update: 2012-10-12