Template-based image retrieval

Abstract

The paper presents a TREE (templates and their relationship extraction and estimation) algorithm for indexing images from picture libraries with more semantics-sensitive meanings. In this approach, each image is represented by a set of templates and their spatial relationships as keys to capture the essence of the image. Each template is characterized by a set of dominant regions, which reflect different appearances of an object at different conditions and can be obtained by the proposed TEA (template extraction and analysis) algorithm through region matching. The STREAM (spatial template relationship extraction and measurement) algorithm is then proposed for obtaining the spatial relations between these extracted templates. Due to the nature of a template, which can represent various appearances of an object at different conditions, the proposed approach can provide better capabilities and flexibilities to capture image contents than other traditional region-based methods. Besides, through maintaining the spatial layout of images, the semantic meanings hidden in the query images can be extracted and lead to significant improvements in the accuracy of image retrieval.