Image segmentation with a hybrid ensemble of one-class support vector machines

Authors:
Bogusław Cyganek
Affiliations:
AGH University of Science and Technology, Kraków, Poland
Venue:
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
Year:
2010

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Abstract

In this paper an efficient method of image segmentation from large data samples is presented Segmentation is stated as a novelty detection problem for which the one-class support vector machines (OC-SVM) are employed However, to improve performance and scalability the input space of samples is first k-means partitioned, and then each partition is independently trained with an OC-SVM This way a parallel structure of expert classifiers is obtained with of a small average number of support vectors and high precision.