Image retrieval for information systems
Thorsten Hermes, Christoph Klauck, Jutta Kreyß, J. Zhang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
In order to retrieve a set of intended images from a huge image archive, human beings think of special contents with respect to the searched scene, like a countryside or a technical drawing. Therefore, in general it is harder to retrieve images by using a syntactical feature- based language than a language which offers the selection of examples concerning color, texture, and contour in combination with natural language concepts. This motivation leads to a content-based image analysis and goes on to a content-based storage and retrieval of images. Furthermore, it is unreasonable for any human being to make the content description for thousands of images manually. From this point of view, the project IRIS (image retrieval for information systems) combines well-known methods and techniques in computer vision and AI in a new way to generate content descriptions of images in a textual form automatically. IRIS retrieves the images by means of text retrieval realized by the SearchManager/6000. The textual description is generated by four sub-steps: feature extraction like colors, textures, and contours, segmentation, and interpretation of part-whole relations. The system is implemented on IBM RS/6000 using AIX. It has already been tested with 350 images.