Using an image-extended relational database to support content-based image retrieval in a PACS

Authors:
Caetano Traina, Jr;Agma J. M. Traina;Myrian R. B. Araújo;Josiane M. Bueno;Fabio J. T. Chino;Humberto Razente;Paulo M Azevedo-Marques
Affiliations:
Computer Science Department, University of São Paulo at Sdo Carlos, Brazil;Computer Science Department, University of São Paulo at Sdo Carlos, Brazil;Computer Science Department, University of São Paulo at Sdo Carlos, Brazil;Computer Science Department, University of São Paulo at Sdo Carlos, Brazil;Computer Science Department, University of São Paulo at Sdo Carlos, Brazil;Computer Science Department, University of São Paulo at Sdo Carlos, Brazil;Science of Image and Medical Physics Center of the Medical School of Ribeirão Preto, University of Sdo Paulo at Ribeirdo Preto, Brazil
Venue:
Computer Methods and Programs in Biomedicine
Year:
2005

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Abstract

This paper presents a new Picture Archiving and Communication System (PACS), called cbPACS, which has content-based image retrieval capabilities. The cbPACS answers range and k-nearest- neighbor similarity queries, employing a relational database manager extended to support images. The images are compared through their features, which are extracted by an image-processing module and stored in the extended relational database. The database extensions were developed aiming at efficiently answering similarity queries by taking advantage of specialized indexing methods. The main concept supporting the extensions is the definition, inside the relational manager, of distance functions based on features extracted from the images. An extension to the SQL language enables the construction of an interpreter that intercepts the extended commands and translates them to standard SQL, allowing any relational database server to be used. By now, the system implemented works on features based on color distribution of the images through normalized histograms as well as metric histograms. Metric histograms are invariant regarding scale, translation and rotation of images and also to brightness transformations. The cbPACS is prepared to integrate new image features, based on texture and shape of the main objects in the image.