Detection of obscured and partially covered objects using partial network matching and an image feature network-based object recognition algorithm

Jeremy Straub

doi:10.1117/12.2050171

29 May 2014 Detection of obscured and partially covered objects using partial network matching and an image feature network-based object recognition algorithm

Jeremy Straub

Author Affiliations +

Proceedings Volume 9072, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX; 90721B (2014) https://doi.org/10.1117/12.2050171
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

An approach to image classification based on the analysis of the network of points generated by an image feature detection algorithm has been proposed. This network-based approach looks at the networks produced by two images and scale and then compare them, making a classification decision. This paper considers techniques to handle the problem posed by input images that are obscured or in which the target is partially covered. These approaches are compared with the base algorithm to assess the impact on performance in the general case, obscured scenarios and obstructed scenarios.

Citation Download Citation

Jeremy Straub "Detection of obscured and partially covered objects using partial network matching and an image feature network-based object recognition algorithm", Proc. SPIE 9072, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX, 90721B (29 May 2014); https://doi.org/10.1117/12.2050171

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