High Atomic Number Liquid Container Identification Based on Combined Invariant Moments and Local Feature
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摘要: 目前液体检查是地铁、机场安检工作中极为迫切的需求。本文提出了一种全新的基于全局和局部特征的高原子序数液体容器识别方法。该方法基于全局区域提取其组合矩特征,在识别初期首先迅速找到与模型库中相似的物品和差异较小的姿态,然后根据局部特征即容器壁投影特征和瓶底特征进行判断和提高识别精度。实验结果证明,该方法很好地结合了目标的整体和局部信息,能够解决容器在与高原子序数物品局部遮挡问题,同时具有较高的识别精度。Abstract: For the security inspection at airports and stations,it is urgently needed to discriminate the liquid examination.We proposed a novel method for high atomic liquid container discrimination based on global and local features.First,we extracted the combined invariant moments based on the global feature,which quickly find a large number of candidates for an efficient recognition.Then local feature identification was made as a second judgment to improve the recognition accuracy of feature detection.The container wall the bottom projection features were chosen as the local feature.Experimental results show that this method combines good global and local target information.This approach can solve the container occlusion problems with a high atomic number materials in partial,and also has high recognition accuracy.
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Keywords:
- image segmentation /
- X-ray images /
- target recognition /
- combined invariant moments /
- local feature
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