Retrieval of 2D vector images by matching Weighted Feature Points

A novel method for content-based 2D vector image retrieval is proposed in this paper. To retrieve vector images, first, the proposed method extracts WFPs (Weighted Feature Points) from vector images. In this extraction process, the method directly accesses the parameters of Bezier curves defining the shapes of vector images and computes WFPs of the images according to these parameters. Second, to a pair of vector images, the method evaluates similarity by matching WFPs using PTD (Proportional Transfer Distance). In the proposed method, vector images are not rasterized, which enables real-time retrieval. As a prototyping, we have implemented a system for sketch-based vector image retrieval. In the system, a sketch is used as a query. To bridge the representation gap between sketches and vector images in a database, the strokes in sketches are approximated with Bezier curves as a pre-process. Using the system and a database containing 1,120 logomarks, we have confirmed the retrieval performance and have discussed the limits of the proposed method.