Scenery Image Segmentation Using Support Vector Machines

Article type: Research Article

Authors: Yu, Yuan-Hui | Chang, Chin-Chen

Affiliations: Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan, 621, R.O.C.

Abstract: This paper presents an effective and efficient method for solving scenery image segmentation by applying the SVMs methodology. Scenery image segmentation is regarded as a data classification problem, and is effectively answered by the proposed method in this paper. Using the model selection in our system architecture, our system is relatively simple compared to other conventional heuristic image segmentation approaches yet demonstrates promising classification results.

Keywords: SVMs, SVM-based classification, scenery image segmentation, model selection,

Journal: Fundamenta Informaticae, vol. 61, no. 3-4, pp. 379-388, 2004