| Title | A Template Matching Background Filtering Method for Millimeter Wave Human Security Image |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Xin, Le, Li, Yuanji, Shang, Shize, Li, Guangrui, Yang, Yuhao |
| Conference Name | 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) |
| Date Published | nov |
| Keywords | actual millimeter wave image, adaptive filtering, adaptive template, background area, background noise, bilateral filtering, filtering theory, human body area, image denoising, image details, image matching, image segmentation, level set algorithm, Level Set Segmentation, matched filters, Metrics, millimeter wave human security image, millimeter wave human security inspection, millimeter wave security image, millimetre wave imaging, Object recognition, objects identification, pubcrawl, Resiliency, Scalability, set theory, template matching, template matching background filtering method, traditional filtering method |
| Abstract | In order to solve the interference of burrs, aliasing and other noises in the background area of millimeter wave human security inspection on the objects identification, an adaptive template matching filtering method is proposed. First, the preprocessed original image is segmented by level set algorithm, then the result is used as a template to filter the background of the original image. Finally, the image after background filtered is used as the input of bilateral filtering. The contrast experiments based on the actual millimeter wave image verifies the improvement of this algorithm compared with the traditional filtering method, and proves that this algorithm can filter the background noise of the human security image, retain the image details of the human body area, and is conducive to the object recognition and location in the millimeter wave security image. |
| DOI | 10.1109/APSAR46974.2019.9048312 |
| Citation Key | xin_template_2019 |
A Template Matching Background Filtering Method for Millimeter Wave Human Security Image