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Adaptive Segmentation of Color Image for Vision Navigation of Mobile Robots.
- Source :
- Advances in Neural Networks - ISNN 2006 (9783540344377); 2006, p523-532, 10p
- Publication Year :
- 2006
-
Abstract
- The self-localization problem is very important when the mobile robot has to move in autonomous way. Among techniques for self-localization, landmark-based approach is preferred for its simplicity and much less memory demanding for descriptions of robot surroundings. Door-plates are selected as visual landmarks. In this paper, we present an adaptive segmentation approach based on Principal Component Analysis (PCA) and scale-space filtering. To speed up the entire color segmentation and use the color information as a whole, PCA is implemented to project tristimulus R, G and B color space to the first principal component (1st PC) axis direction and scale-space filtering is used to get the centers of color classes. This method has been tested in the color segmentation of door-plate images captured by mobile robot CASIA-1. Experimental results are provided to demonstrate the effectiveness of this proposed method. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISBNs :
- 9783540344377
- Database :
- Supplemental Index
- Journal :
- Advances in Neural Networks - ISNN 2006 (9783540344377)
- Publication Type :
- Book
- Accession number :
- 32862240
- Full Text :
- https://doi.org/10.1007/11760023_77