Region-based method for passive millimeter-wave imaging detection

Yayun Cheng; Xun Tian; Dong Zhu

doi:10.1109/CAMA56352.2022.10002443

Region-based method for passive millimeter-wave imaging detection

Yayun Cheng^*
, Xun Tian
, Dong Zhu

^*Corresponding author for this work

School of Electronics and Information Engineering, Harbin Institute of Technology
Huazhong University of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Passive millimeter-wave (PMMW) imaging is a powerful approach for detecting concealed objects underneath clothing. Object detection is an important issue in personnel security inspection. Much previous research has been carried out based on the gray-scale image of brightness temperature. Existing methods are mainly based on single-pixel processing. In this paper, we present a region-based method for concealed object detection. By combining superpixel segmentation and Fisher vectors, a new indicator, regional Fisher vector (RFV), is used to generate binary detection. Several imaging data of a typical personnel security inspection scenario are used to verify the proposed method.

Original language	English
Title of host publication	2022 IEEE Conference on Antenna Measurements and Applications, CAMA 2022
Publisher	Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781665490375
DOIs	https://doi.org/10.1109/CAMA56352.2022.10002443
State	Published - 2022
Externally published	Yes
Event	2022 IEEE Conference on Antenna Measurements and Applications, CAMA 2022 - Guangzhou, China Duration: 14 Dec 2022 → 17 Dec 2022

Publication series

Name	IEEE Conference on Antenna Measurements and Applications, CAMA
Volume	2022-December
ISSN (Print)	2474-1760
ISSN (Electronic)	2643-6795

Conference

Conference	2022 IEEE Conference on Antenna Measurements and Applications, CAMA 2022
Country/Territory	China
City	Guangzhou
Period	14/12/22 → 17/12/22

Keywords

Fisher vector
Gaussian mixture model
object detection
passive millimeter-wave
personnel security screening

Access to Document

10.1109/CAMA56352.2022.10002443

Cite this

@inproceedings{8684eef5d0bf4751bf989bb840761270,

title = "Region-based method for passive millimeter-wave imaging detection",

abstract = "Passive millimeter-wave (PMMW) imaging is a powerful approach for detecting concealed objects underneath clothing. Object detection is an important issue in personnel security inspection. Much previous research has been carried out based on the gray-scale image of brightness temperature. Existing methods are mainly based on single-pixel processing. In this paper, we present a region-based method for concealed object detection. By combining superpixel segmentation and Fisher vectors, a new indicator, regional Fisher vector (RFV), is used to generate binary detection. Several imaging data of a typical personnel security inspection scenario are used to verify the proposed method.",

keywords = "Fisher vector, Gaussian mixture model, object detection, passive millimeter-wave, personnel security screening",

author = "Yayun Cheng and Xun Tian and Dong Zhu",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Conference on Antenna Measurements and Applications, CAMA 2022 ; Conference date: 14-12-2022 Through 17-12-2022",

year = "2022",

doi = "10.1109/CAMA56352.2022.10002443",

language = "英语",

series = "IEEE Conference on Antenna Measurements and Applications, CAMA",

publisher = "Institute of Electrical and Electronics Engineers",

booktitle = "2022 IEEE Conference on Antenna Measurements and Applications, CAMA 2022",

address = "美国",

}

Cheng, Y, Tian, X & Zhu, D 2022, Region-based method for passive millimeter-wave imaging detection. in 2022 IEEE Conference on Antenna Measurements and Applications, CAMA 2022. IEEE Conference on Antenna Measurements and Applications, CAMA, vol. 2022-December, Institute of Electrical and Electronics Engineers, 2022 IEEE Conference on Antenna Measurements and Applications, CAMA 2022, Guangzhou, China, 14/12/22. https://doi.org/10.1109/CAMA56352.2022.10002443

Region-based method for passive millimeter-wave imaging detection. / Cheng, Yayun; Tian, Xun; Zhu, Dong.
2022 IEEE Conference on Antenna Measurements and Applications, CAMA 2022. Institute of Electrical and Electronics Engineers, 2022. (IEEE Conference on Antenna Measurements and Applications, CAMA; Vol. 2022-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Region-based method for passive millimeter-wave imaging detection

AU - Cheng, Yayun

AU - Tian, Xun

AU - Zhu, Dong

PY - 2022

Y1 - 2022

N2 - Passive millimeter-wave (PMMW) imaging is a powerful approach for detecting concealed objects underneath clothing. Object detection is an important issue in personnel security inspection. Much previous research has been carried out based on the gray-scale image of brightness temperature. Existing methods are mainly based on single-pixel processing. In this paper, we present a region-based method for concealed object detection. By combining superpixel segmentation and Fisher vectors, a new indicator, regional Fisher vector (RFV), is used to generate binary detection. Several imaging data of a typical personnel security inspection scenario are used to verify the proposed method.

AB - Passive millimeter-wave (PMMW) imaging is a powerful approach for detecting concealed objects underneath clothing. Object detection is an important issue in personnel security inspection. Much previous research has been carried out based on the gray-scale image of brightness temperature. Existing methods are mainly based on single-pixel processing. In this paper, we present a region-based method for concealed object detection. By combining superpixel segmentation and Fisher vectors, a new indicator, regional Fisher vector (RFV), is used to generate binary detection. Several imaging data of a typical personnel security inspection scenario are used to verify the proposed method.

KW - Fisher vector

KW - Gaussian mixture model

KW - object detection

KW - passive millimeter-wave

KW - personnel security screening

UR - https://www.scopus.com/pages/publications/85148289580

U2 - 10.1109/CAMA56352.2022.10002443

DO - 10.1109/CAMA56352.2022.10002443

M3 - 会议稿件

AN - SCOPUS:85148289580

T3 - IEEE Conference on Antenna Measurements and Applications, CAMA

BT - 2022 IEEE Conference on Antenna Measurements and Applications, CAMA 2022

PB - Institute of Electrical and Electronics Engineers

T2 - 2022 IEEE Conference on Antenna Measurements and Applications, CAMA 2022

Y2 - 14 December 2022 through 17 December 2022

ER -

Region-based method for passive millimeter-wave imaging detection

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Keywords

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