Study of Automatic Detection of Concealed Targets in Passive Terahertz Images for Intelligent Security Screening
Study of Automatic Detection of Concealed Targets in Passive Terahertz Images for Intelligent Security Screening
复制标题
被动太赫兹图像隐蔽目标自动检测智能安检研究
DOI：
10.1109/tthz.2018.2889407
复制
发表时间：
2019-03-01
影响因子：
3.2
通讯作者：
Fang, Guangyou
中科院分区：
文献类型：
--
作者：
Li, Rui;Li, Chao;Fang, Guangyou
从图像中自动提取感兴趣的目标是基于成像技术的安检系统自动检测和识别的基础。由于太赫兹（THz）成像系统的信噪比（SNR）较低，使得被动THz成像系统中目标的自动检测面临着巨大的挑战，也是迫切需要解决的问题。本文首先研究了一种利用被动太赫兹图像的“块统计均匀性”特性自动检测被动太赫兹图像中隐藏目标的综合方法。针对传统的基于梯度边缘算子的“特征区域”分解方法在低信噪比、边界模糊的被动图像中应用不成功的缺点，建立了基于“拟合能量”泛函相对于“表面函数”最小化的“特征区域”分解理论模型.在已有理论基础上，利用收敛的“面函数”在不同“特征区域”上的显著差异，进一步提出了一种三步自动检测算法，自动提取所有隐藏目标的数量、位置和形状，每个目标的形状以顺时针方向排列的轮廓点序列表示。在0.2THz波段的大量实验结果表明，该方法即使在低信噪比的单通道状态证明系统中，也具有95%左右的检测精度和较好的实时性。本文的定理、算法和结果在无人值守的智能安检系统中具有重要的应用价值。
The automatic extraction of the targets in which we are interested from a given image is the fundamental of the automatic detection and identification for security screening systems based on imaging technologies. Suffering from the comparatively low signal-to-noise ratio (SNR), the automatic detection of targets in a passive terahertz (THz) imaging system facing great challenges, but in urgent necessary. In this paper, a comprehensive method for automatic detection of concealed targets in passive THz image by making the best use of the “block statistics uniformity” properties of the passive images is first studied. A theoretical model for the “featured regions” decomposition based on the minimization of a “fit energy” functional with respect to a “surface function” is established, to overcome the drawbacks of conventional methods with gradient-based edge operators for their unsuccessful application in low SNR passive images with blurred boundaries. Based on earlier theoretical basis and taking advantages of the distinguished contrasts of the convergent “surface function” in different “featured regions,” an automatic detection algorithm with three steps was further developed to automatically extract the number, the locations and the shapes of all the concealed targets, with the shape of each target derived as the contour point series arranged in clockwise direction. With plenty of experimental results in 0.2 THz band, it is found that, the proposed method has high detection accuracy about 95% with quite good realtime performance, even for the single channel proof-of-state system with low SNR. The theorem, algorithm, and results, in this paper, may have important applications in unmanned and intelligent security screening systems without any artificial interventions.