A Ground-Truth Training Set for Hierarchical Clustering in Content-Based Image Retrieval

Progress in Content-Based Image Retrieval (CBIR) is ham-pered by the absence of well-documented and validated test-sets that provide ground-truth for the performance evaluation of image indexing, retrieval and clustering tasks. For quick access to large (tenthousands or millions of images) digital image collections a hierarchically structured indexing or browsing mechanism based on clusters of similar images at various coarse to fine levels is highly wanted. The Leiden 19th-Century Portrait Database (LCPD), that consists of over 16,000 scanned studio portraits (so-called Cartes de Visite CdV), happens to have a clearly delineated set of clusters in the studio logo backside images. Clusters of similar or semantically identical logos can also be formed on a number of levels that show a clear hierarchy. The Leiden Imaging and Multi-media Group is constructing a CD-ROM with a well-documented set of studio portraits and logos that can serve as ground-truth for feature performance evaluation...