Analyst-trainable fusion algorithms for surveillance applications

Richard L. Delanoy; Richard T. Lacoss

doi:10.1117/12.321870

15 September 1998 Analyst-trainable fusion algorithms for surveillance applications

Richard L. Delanoy, Richard T. Lacoss

Proceedings Volume 3370, Algorithms for Synthetic Aperture Radar Imagery V; (1998) https://doi.org/10.1117/12.321870
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

The Toolkit for Image Mining (TIM) is a prototype software environment that enables users with no knowledge of image processing and machine learning to interactively create image search and image analysis tools. TIM is being used as a testbed for the study of issues related to data fusion and on-the-fly training in the context of target recognition in DARPA's Semi-Automated IMINT Processing system. Experiments done in this environment suggest that on-the-fly training is technically feasible, need not pose an extra burden on image analysts, and can increase the flexibility and adaptability of surveillance algorithms.

Citation Download Citation

Richard L. Delanoy and Richard T. Lacoss "Analyst-trainable fusion algorithms for surveillance applications", Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); https://doi.org/10.1117/12.321870

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