Scene classification based on multi-resolution orientation histogram of gabor features

Abstract

This paper presents a scene classification method based on multi-resolution orientation histogram. In recent years, some scene classification methods have been proposed because scene category information is used as the context for object detection and recognition. Recent studies uses the local parts without topological information. However, the middle size features with rough topological information are more effective for scene classification. For this purpose, we use orientation histogram with rough topological information. Since we do not the appropriate subregion size for computing orientation histogram, various subregion sizes are prepared, and multi-resolution orientation histogram is developed. Support Vector Machine is used to classify the scene category. To improve the accuracy, the similarity between orientation histogram on the same subregion is used effectively. The proposed method is evaluated with the same database and protocol as the recent studies. We confirm that the proposed method outperforms the recent scene classification methods. © 2008 Springer-Verlag Berlin Heidelberg.