Journal of Infrared and Millimeter Waves, Volume. 40, Issue 6, 738(2021)
Concealed Object Detection in Millimeter Wave Image Based on Global Correlation of Multi-level Features in Cross-section Sequence
Fig. 1. MMW imaging system (a)prototype of Sim-Image,(b)examples of contraband
Fig. 3. Examples of MMW image processing (a)、(c)2D MMW image with ground truth of difficult case 1 and 2,(b)、(d)illustration of the sampling process
Fig. 4. Analysis results of difficult case 1 intensity distribution curve of sampling point along depth direction of (a)object and (b)background,(c)comparison of the average intensity distribution curve of the object and the background area along the depth direction,(d-f)example of MMW cross-section corresponding to interval I,II and III
Fig. 5. Analysis results of difficult case 2 intensity distribution curve of sampling point along depth direction of (a)object and (b)background
Fig. 6. Comparison of intensity distribution between object and noise (a)(e)2D MMW image with sampling area,intensity distribution curve in depth direction of (b)(f)object,and (c-d)、(g-h)noise
Fig. 10. Illustration of our dataset (a)3D MMW image,(b)the projection in the y-direction,(c)the projection in the x-direction,(d)statistical analysis result of the dataset
Fig. 12. The visualization results of the CAM of feature map (a)the image to be measured with ground truth,(b)the salient region of the feature map obtained by the traditional method,(c)the salient region of the feature map obtained by the proposed method
Fig. 13. Comparison of CAM visualization of feature maps of cross-section (a-b)the side view of 3D MMW image to be measured,CAM results and the side view (c)before,and (d)after Bi-CLSTM
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Wan-Ting HE, Bo ZHANG, Bin WANG, Xiao-Wei SUN, Ming-Hui YANG, Xiao-Feng WU. Concealed Object Detection in Millimeter Wave Image Based on Global Correlation of Multi-level Features in Cross-section Sequence[J]. Journal of Infrared and Millimeter Waves, 2021, 40(6): 738
Category: Research Articles
Received: Mar. 8, 2021
Accepted: --
Published Online: Feb. 16, 2022
The Author Email: Xiao-Feng WU (xiaofengwu@fudan.edu.cn)