School of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, Bundoora, Victoria, Australia.
PLoS One. 2011;6(9):e25621. doi: 10.1371/journal.pone.0025621. Epub 2011 Sep 29.
Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository.
自动目标识别依赖于从逼真成像中快速提取实时目标的特征,从而实现目标模式的高效识别。为了实现这一目标,通过使用最小的计算资源高速捕获关键空间特征,探索了二进制模式的十字形图作为观察到的目标的潜在特征。基于所提出的模式识别概念实现了目标识别,并对其精度和召回性能进行了严格测试。我们的结论是,十字形图能够生成目标的数字指纹,该指纹与目标库中具有其身份的模式的特征高效且有效地相关联。