STUDY ON IMAGE CLASSIFICATION BASED ON SVM AND THE FUSION OF MULTIPLE FEATURES

Dequan Zheng, Tiejun Zhao, Sheng Li, Yufeng Li

Abstract

In this paper, an adaptive feature-weight adjusted image classification method is proposed, which is based on the SVM and the fusion of multiple features. Firstly, classifier was separately constructed for each image feature, then automatically learn the weight coefficient of each feature by training data set and the classifiers constructed. At last, a complexity classifier is created by combining the separate classifier and the corresponding weight coefficient. The experiment result showed that our scheme improved the performance of image classification and had adaptive ability comparing with general approach. Moreover, the scheme has certain robustness because of avoiding the impact brought by various dimension of each feature.

References

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Paper Citation


in Harvard Style

Zheng D., Zhao T., Li S. and Li Y. (2009). STUDY ON IMAGE CLASSIFICATION BASED ON SVM AND THE FUSION OF MULTIPLE FEATURES . In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-85-2, pages 81-85. DOI: 10.5220/0001864200810085


in Bibtex Style

@conference{iceis09,
author={Dequan Zheng and Tiejun Zhao and Sheng Li and Yufeng Li},
title={STUDY ON IMAGE CLASSIFICATION BASED ON SVM AND THE FUSION OF MULTIPLE FEATURES},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2009},
pages={81-85},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001864200810085},
isbn={978-989-8111-85-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - STUDY ON IMAGE CLASSIFICATION BASED ON SVM AND THE FUSION OF MULTIPLE FEATURES
SN - 978-989-8111-85-2
AU - Zheng D.
AU - Zhao T.
AU - Li S.
AU - Li Y.
PY - 2009
SP - 81
EP - 85
DO - 10.5220/0001864200810085