论文信息 - Detection of small targets and their characterization based on their formation using an image feature network-based object recognition algorithm

Detection of small targets and their characterization based on their formation using an image feature network-based object recognition algorithm

Small target detection and classification is problematic. For targets that operate as part of a cluster, classification can be performed based on the characteristics of the cluster’s operations, instead of trying to identify an individual clustermember directly. This paper presents an algorithm for object identification based on comparing networks of point-topoint distances between features identified by an image feature detection algorithm. It discusses the alterations required to make the algorithm suitable for performing cluster-formation based characterization of small targets from point or near-point source data. An analysis of the algorithm’s performance is presented and it efficacy for this application assessed.

Jeremy Straub

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