Graph/Image Legend Retrieval

Abstract

There are many content-based retrieval methods for image databases, however, none of them coped with graph and image simultaneously. Moreover, existing graph retrieval methods handled for a silhouette or a graph component rather than the whole graph. Hence, it is the goal of this paper to propose a graph/image legend retrieval method. The proposed method consists of two phases: legend extract and legend retrieval. The features used in our method include aspect ratio, number of legend components and spatial histograms of pixel number, border length and gray level. Since the processed legends can be properly divided into two categories: graph and image, type-based matching is adopted to evaluate the similarity between the query legend and each database legend using different similarity measures according to the type of the query legend which can be automatically determined. In this way, the correct legend can be retrieved. The effectiveness and practicability of the proposed method have been demonstrated by various experiments.