MVTec Software GmbH

HERON - Middleware for Image Retrieval Using Graphical Features Extracted by HALCON

Finding images in digital libraries or large image archives without detailed knowledge about domain, iconography or the specific kind of objects depicted, is the aim of the interdisciplinary HERON project. HERON is an acronym for heraldry online, indicating that the project's first practical application area is about heraldry, the science of coats of arms. Though heraldry represents an important branch of art-historical research, the project's vision is not restricted to the field of art-history, but may serve various applications with need of image databases, as for example medical imaging or collections of trademark and designs. The HERON framework project is carried out by the Institute of Computer Science and the library of the University of Augsburg.

 

The HERON prototype was presented for the first time at the computer trade fair SYSTEMS '99 in Munich. It features an innovative middleware for multimedia queries in large image archives and digital libraries. This middleware is based on industrial standards like IBM DB2 Universal Database with relational extenders for images and text, JDBC and Java. Complex multimedia retrievals may contain queries on image content, e.g. colors, textures or shapes, as well as conventional text-based queries including thesauri searches. These complex multi-feature queries are split into smaller parts that can be handled by the underlying database systems. The ranked result sets of each system can be merged efficiently using a new algorithm that has been proposed for patenting. For digitization of large image collections promising techniques for the (semi-) automatic segmentation of image objects have been developed as a basis for advanced shape matching.

 

Within the HERON project HALCON is used for preparing images when adding them to the multimedia database. HALCON is used for the image segmentation and for extracting graphical features in the heraldic images that make it possible to efficiently process multimedia queries in large databases.

 

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