Tuning a CBIR system for vector images
Tania Di Mascio, Marco Francesconi, Daniele Frigioni, Laura Tarantino · 2004
This paper presents a system supporting tuning and evaluation of a Content-Based Image Retrieval (CBIR) engine for vector images, by a graphical interface providing query-by-sketch and query-by-example interaction with query results, and analysis of result quality. Vector images are first modelled as an inertial system and then they are associated with descriptors representing visual features invariant to affine transformation. To support requirements of different application domains, the engine offers a variety of moment sets as well as difierent metrics for similarity computation. The graphical interface offers tools that helps in the selection of criteria and parameters necessary to tune the system to a specific application domain.