Support vector machines (SVM) for color image segmentation with applications to mobile robot localization problems

Authors:
An-Min Zou;Zeng-Guang Hou;Min Tan
Affiliations:
Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China
Venue:
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
Year:
2005

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Abstract

In autonomous mobile robot industry, the landmark-based localization method is widely used in which the landmark recognition plays an important role. The landmark recognition using visual sensors relies heavily on the quality of the image segmentation. In this paper, we use seat numbers as the landmarks, and it is of great importance to the seat number recognition that correctly segment the number regions from images. To perform this assignment, the support vector machine method is adopted to solve the color image segmentation problems because of its good generalization ability. The proposed method has been used for the mobile robot localization problems, and experimental results show that the proposed method can bring robust performance in practice.