Concealed Object Detection for Millimeter-wave Images with Normalized Accumulation Map

2020 ◽  
pp. 1-1
Author(s):  
Chen Wang ◽  
Jun Shi ◽  
Zenan Zhou ◽  
Liang Li ◽  
Yuanyuan Zhou ◽  
...  
2019 ◽  
Vol 66 (12) ◽  
pp. 9909-9917 ◽  
Author(s):  
Ting Liu ◽  
Yao Zhao ◽  
Yunchao Wei ◽  
Yufeng Zhao ◽  
Shikui Wei

2011 ◽  
Author(s):  
Christian Zech ◽  
Axel Hülsmann ◽  
Ingmar Kallfass ◽  
Axel Tessmann ◽  
Martin Zink ◽  
...  

2002 ◽  
Author(s):  
Stuart E. Clark ◽  
John A. Lovberg ◽  
Christopher A. Martin ◽  
Joseph A. Galliano, Jr.

2011 ◽  
Vol 19 (3) ◽  
pp. 2530 ◽  
Author(s):  
Seokwon Yeom ◽  
Dong-Su Lee ◽  
Jung-Young Son ◽  
Min-Kyoo Jung ◽  
YuShin Jang ◽  
...  

Author(s):  
Y. Chen ◽  
L. Pang ◽  
H. Liu ◽  
X. Xu

PMMW imaging system can create interpretable imagery on the objects concealed under clothing, which gives the great advantage to the security check system. Paper addresses wavelet fusion to detect concealed objects using passive millimeter wave (PMMW) sequence images. According to PMMW real-time imager acquired image characteristics and storage methods,firstly, using the sum of squared difference (SSD) as the image-related parameters to screen the sequence images. Secondly, the selected images are optimized using wavelet fusion algorithm. Finally, the concealed objects are detected by mean filter, threshold segmentation and edge detection. The experimental results show that this method improves the detection effect of concealed objects by selecting the most relevant images from PMMW sequence images and using wavelet fusion to enhance the information of the concealed objects. The method can be effectively applied to human body concealed object detection in millimeter wave video.


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