Abstract
In recent years, terahertz imaging systems and techniques have been developed and have gradually become a leading frontier field. With the advantages of low radiation and clothing-penetrable, terahertz imaging technology has been widely used for the detection of concealed weapons or other contraband carried on personnel at airports and other secure locations. This paper aims to detect these concealed items with deep learning method for its well detection performance and real-time detection speed. Based on the analysis of the characteristics of terahertz images, an effective detection system is proposed in this paper. First, a lots of terahertz images are collected and labeled as the standard data format. Secondly, this paper establishes the terahertz classification dataset and proposes a classification method based on transfer learning. Then considering the special distribution of terahertz image, an improved faster region-based convolutional neural network (Faster R-CNN) method based on threshold segmentation is proposed for detecting human body and other objects independently. Finally, experimental results demonstrate the effectiveness and efficiency of the proposed method for terahertz image detection.
Highlights
In response to an increasing threat of terrorism, personnel surveillance at security checkpoints is becoming increasingly important [1,2]
After solving the classification problem, considering the particularity of terahertz images, we propose an improved Faster R-convolutional neural networks (CNN) method based on threshold segmentation for the human body and other objects' detection
At the same time, compared with synthetic aperture radar (SAR) image, terahertz image is not affected by the same time, compared with SAR image, terahertz image is not affected by the multiplicative nature of multiplicative nature of the speckle, the background of terahertz image represents clearer the speckle, the background of terahertz image represents clearer and an intuitive detection and an intuitive detection method is to use the threshold segmentation to locate the human body
Summary
In response to an increasing threat of terrorism, personnel surveillance at security checkpoints is becoming increasingly important [1,2]. Typical detection systems such as metal detectors for personnel and X-ray systems for hand-carried items are effective and have a lot of shortcomings. As a result of that, X-ray systems are only used to detect hand-carried items. Similar to the synthetic aperture radar (SAR), by synthesizing the real aperture into a larger virtual aperture [7,8,9,10], terahertz active imaging system could obtain clear human images which reveals the reflection characteristics of the concealed objects carried on human body. After getting the human image, it’s very important and meaningful to decide whether dangerous objects are carried or determine corresponding categories of these objects
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