Developing a Shape-and-Composition CBIR Thesaurus for the Traditional Chinese Landscape

Abstract

In the past decade, content-based image retrieval (CBIR) has been investigated extensively. Current research has suggested that the two elemental issues in CBIR, feature extraction and similarity measures, tend to be domain-specific. This paper develops a shape-and-composition CBIR thesaurus for Chinese landscape paintings dating from the Song to Qing periods (960-1911). The features were extracted from studying approximately 1,000 Chinese landscape paintings. The thesaurus emphasizes discrimination among object types in order to improve retrieval of relevant images. Therefore, it adopts not only basic shapes but also line and shape combinations. Furthermore, special shapes are developed for those object types that are either unique to Chinese art and culture, or are a peculiar shape that cannot easily be abstracted into basic shapes. Although it is domain-specific, the approach of developing and classifying the thesaurus may be applicable to CBIR of non-Chinese art images and CBIR in general.