Supervised learning of tools for content-based search of image databases

Richard L. Delanoy

doi:10.1117/12.234796

13 March 1996 Supervised learning of tools for content-based search of image databases

Richard L. Delanoy

Proceedings Volume 2670, Storage and Retrieval for Still Image and Video Databases IV; (1996) https://doi.org/10.1117/12.234796
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States

Abstract

A computer environment, called the Toolkit for Image Mining (TIM), is being developed with the goal of enabling users with diverse interests and varied computer skills to create search tools for content-based image retrieval and other pattern matching tasks. Search tools are generated using a simple paradigm of supervised learning that is based on the user pointing at mistakes of classification made by the current search tool. As mistakes are identified, a learning algorithm uses the identified mistakes to build up a model of the user's intentions, construct a new search tool, apply the search tool to a test image, display the match results as feedback to the user, and accept new inputs from the user. Search tools are constructed in the form of functional templates, which are generalized matched filters capable of knowledge- based image processing. The ability of this system to learn the user's intentions from experience contrasts with other existing approaches to content-based image retrieval that base searches on the characteristics of a single input example or on a predefined and semantically- constrained textual query. Currently, TIM is capable of learning spectral and textural patterns, but should be adaptable to the learning of shapes, as well. Possible applications of TIM include not only content-based image retrieval, but also quantitative image analysis, the generation of metadata for annotating images, data prioritization or data reduction in bandwidth-limited situations, and the construction of components for larger, more complex computer vision algorithms.

Citation Download Citation

Richard L. Delanoy "Supervised learning of tools for content-based search of image databases", Proc. SPIE 2670, Storage and Retrieval for Still Image and Video Databases IV, (13 March 1996); https://doi.org/10.1117/12.234796

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