Interactive image quantification tools in nuclear material forensics

Reid Porter; Christy Ruggiero; Don Hush; Neal Harvey; Patrick Kelly; Wayne Scoggins; Lav Tandon

doi:10.1117/12.877319

7 February 2011 Interactive image quantification tools in nuclear material forensics

Reid Porter, Christy Ruggiero, Don Hush, Neal Harvey, Patrick Kelly, Wayne Scoggins, Lav Tandon

Author Affiliations +

Proceedings Volume 7877, Image Processing: Machine Vision Applications IV; 787708 (2011) https://doi.org/10.1117/12.877319
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

Morphological and microstructural features visible in microscopy images of nuclear materials can give information about the processing history of a nuclear material. Extraction of these attributes currently requires a subject matter expert in both microscopy and nuclear material production processes, and is a time consuming, and at least partially manual task, often involving multiple software applications. One of the primary goals of computer vision is to find ways to extract and encode domain knowledge associated with imagery so that parts of this process can be automated. In this paper we describe a user-in-the-loop approach to the problem which attempts to both improve the efficiency of domain experts during image quantification as well as capture their domain knowledge over time. This is accomplished through a sophisticated user-monitoring system that accumulates user-computer interactions as users exploit their imagery. We provide a detailed discussion of the interactive feature extraction and segmentation tools we have developed and describe our initial results in exploiting the recorded user-computer interactions to improve user productivity over time.

Citation Download Citation

Reid Porter, Christy Ruggiero, Don Hush, Neal Harvey, Patrick Kelly, Wayne Scoggins, and Lav Tandon "Interactive image quantification tools in nuclear material forensics", Proc. SPIE 7877, Image Processing: Machine Vision Applications IV, 787708 (7 February 2011); https://doi.org/10.1117/12.877319

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