Binary histogram in image classification for retrieval purposes

Abstract

Image retrieval can be considered as a classification problem. Classification is usually based on some image features. In the feature extraction image segmentation is commonly used. In this paper we introduce a new feature for image classification for retrieval purposes. This feature is based on the gray level histogram of the image. The feature is called binary histogram and it can be used for image classification without segmentation. Binary histogram can be used for image retrieval as such by using similarity calculation. Another approach is to extract some features from it. In both cases indexing and retrieval do not require much computational time. We test the similarity measurement and the feature-based retrieval by making classification experiments. The proposed features are tested using a set of paper defect images, which are acquired from an industrial imaging application.