Paper
23 March 1995 Image retrieval for information systems
Thorsten Hermes, Christoph Klauck, Jutta Kreyss, J. Zhang
Author Affiliations +
Proceedings Volume 2420, Storage and Retrieval for Image and Video Databases III; (1995) https://doi.org/10.1117/12.205310
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States
Abstract
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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thorsten Hermes, Christoph Klauck, Jutta Kreyss, and J. Zhang "Image retrieval for information systems", Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, (23 March 1995); https://doi.org/10.1117/12.205310
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Cited by 46 scholarly publications.
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KEYWORDS
Image retrieval

Image segmentation

Image analysis

Object recognition

Edge detection

Feature extraction

IRIS Consortium

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