Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 193-198, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-193-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 193-198, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-193-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

WAVELET FUSION FOR CONCEALED OBJECT DETECTION USING PASSIVE MILLIMETER WAVE SEQUENCE IMAGES

Y. Chen, L. Pang, H. Liu, and X. Xu Y. Chen et al.
  • Beijing University of Civil Engineering and Architecture No.15 , Yongyuanlu Road, DaXing District, 102600, Beijing, China

Keywords: passive millimeter wave, sequence images, sum of squared difference, wavelet fusion, concealed object detection

Abstract. 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.