Danny Gibbins

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— Traditionally, Inverse Synthetic Aperture Radar (ISAR) image frames are classified individually in an automatic target recognition system. When information from different image frames is combined, it is usually in the context of time-averaging to remove statistically independent noise fluctuations between images. The sea state induced variability of the(More)
In this paper we present a methodical evaluation of the performance of a new and two traditional approaches to automatic target recognition (ATR) based on silhouette representation of objects. Performance is evaluated under the simulated conditions of imperfect localization by a region of interest (ROI) algorithm (resulting in clipping and scale changes) as(More)
In this paper, we present a method for extracting salient local features from 3D models using surface curvature which has application to 3D object recognition. In the developed technique, the amount of curvature at a point is specified by a positive number known as the curvedness. This value is invariant to rotation as well as translation. A local(More)
This paper presents an investigation of ISAR image classification based on a comparison of range-Doppler imagery to 3D ship reference models. This comparison is performed in the image domain by estimating the motion of a sequency of ISAR images, generating 3D reference models corresponding to the same motion and matching the models with the given ISAR(More)