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Multiband Image Segmentation and Object Recognition for Understanding Road Scenes | IEEE Journals & Magazine | IEEE Xplore

Multiband Image Segmentation and Object Recognition for Understanding Road Scenes


Abstract:

This paper presents a novel method for semantic segmentation and object recognition in a road scene using a hierarchical bag-of-textons method. Current driving-assistance...Show More

Abstract:

This paper presents a novel method for semantic segmentation and object recognition in a road scene using a hierarchical bag-of-textons method. Current driving-assistance systems rely on multiple vehicle-mounted cameras to perceive the road environment. The proposed method relies on integrated color and near-infrared images and uses the hierarchical bag-of-textons method to recognize the spatial configuration of objects and extract contextual information from the background. The histogram of the hierarchical bag-of-textons is concatenated to textons extracted from a multiscale grid window to automatically learn the spatial context for semantic segmentation. Experimental results show that the proposed method has better segmentation accuracy than the conventional bag-of-textons method. By integrating it with other scene interpretation systems, the proposed system can be used to understand road scenes for vehicle environment perception.
Published in: IEEE Transactions on Intelligent Transportation Systems ( Volume: 12, Issue: 4, December 2011)
Page(s): 1423 - 1433
Date of Publication: 21 July 2011

ISSN Information:


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