Multi-Target Detection of Low-Illuminance Scene Based on Polarization Image

XUN Huasheng; ZHANG Jingjing; LIU Xiao; LI Teng; NIAN Fudong; ZHANG Xin

Volume 44 Issue 5

May 2022

Turn off MathJax

Article Contents

Abstract

References

Infrared Technology > 2022 > 44(5): 483-491.

XUN Huasheng, ZHANG Jingjing, LIU Xiao, LI Teng, NIAN Fudong, ZHANG Xin. Multi-Target Detection of Low-Illuminance Scene Based on Polarization Image[J]. Infrared Technology , 2022, 44(5): 483-491.

Citation:

XUN Huasheng, ZHANG Jingjing, LIU Xiao, LI Teng, NIAN Fudong, ZHANG Xin. Multi-Target Detection of Low-Illuminance Scene Based on Polarization Image[J]. Infrared Technology , 2022, 44(5): 483-491.

Citation:

XUN Huasheng, ZHANG Jingjing, LIU Xiao, LI Teng, NIAN Fudong, ZHANG Xin. Multi-Target Detection of Low-Illuminance Scene Based on Polarization Image[J]. Infrared Technology , 2022, 44(5): 483-491.

PDF (3047 KB)

Multi-Target Detection of Low-Illuminance Scene Based on Polarization Image

XUN Huasheng^{1, 2,},
ZHANG Jingjing^{1, 2, 3, ,},
LIU Xiao³,
LI Teng^{1, 2},
NIAN Fudong^{1, 4},
ZHANG Xin^{1, 2}

1.
Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, Hefei 230601, China
2.
Anhui Province Key Laboratory of Polarization Detection Technology, Hefei 230031, China
3.
Key Laboratory of Optical Calibration and Characterization, Chinese Academy of Sciences, Hefei 230031, China
4.
School of Advanced Manufacturing Engineering, Hefei University, Hefei 230601, China

More Information

Received Date: June 14, 2021
Revised Date: August 02, 2021

Graphical Abstract

Abstract

Abstract

Polarized light reflection information can directly invert the intrinsic characteristics of a target and has strong anti-interference characteristics in the transmission process. Thus, polarization imaging technology can be applied to the fields of intelligent monitoring and traffic monitoring in various complex environments. In recent years, deep-neural-network methods for interpreting image detection targets have been developed rapidly and widely used in various fields of image processing. In this study, a vehicle multi-target detection algorithm based on polarized images and deep learning is proposed. First, the target polarization degree image can be obtained by acquiring the polarization image in real time and analyzing the polarization information. Second, to enhance the high contrast between the detection targets and the background in the polarization image, channel attention and spatial attention are introduced into the backbone network to improve the ability of the network features to perform adaptive learning. In addition, the K-means algorithm is used to perform clustering analysis on the target location information, thereby increasing the network's learning speed in the polarization image and improving the progress of target detection. The experimental results show that this method is effective and fast for vehicle detection in complex scenes with low illumination. This method combines the advantages of polarization imaging and deep-learning target detection and has substantial application scope in road vehicle target detection, recognition, and tracking.
- polarization image,
- neural network,
- YOLO v5s,
- multi-target detection,
- attention mechanism

FullText(HTML)

References (21)

References

[1]	于洵, 杨烨, 姜旭, 等. 基于偏振光谱成像的目标识别方法研究[J]. 应用光学, 2016, 37(4): 537-541. https://www.cnki.com.cn/Article/CJFDTOTAL-YYGX201604008.htm YU Xun, YANG Ye, JIANG Xu, et al. Recognition of camouflage targets by polarization spectral imaging system[J]. Journal of Applied Optics, 2016, 37(4): 537-541. https://www.cnki.com.cn/Article/CJFDTOTAL-YYGX201604008.htm
[2]	李从利, 薛松, 陆文骏, 等. 雾天条件下偏振解析成像质量评价[J]. 中国图象图形学报, 2017, 22(3): 366-375. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB201703011.htm LI Congli, XUE Song, LU Wenjun, et al. Quality assessment of polarization imaging under foggy[J]. Journal of Image and Graphics, 2017, 22(3): 366-375. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB201703011.htm
[3]	李小明, 黄勤超. 沙漠背景下红外偏振图像目标检测方法[J]. 红外技术, 2016, 38(9): 779-782, 792. http://hwjs.nvir.cn/article/id/hwjs201609012 LI Xiaoming, HUANG Qinchao. Target detection for infrared polarization image in the background of desert[J]. Infrared Technology, 2016, 38(9): 779-782, 792. http://hwjs.nvir.cn/article/id/hwjs201609012
[4]	张荣, 李伟平, 莫同. 深度学习研究综述[J]. 信息与控制, 2018, 47(4): 385-397. https://www.cnki.com.cn/Article/CJFDTOTAL-XXYK201804002.htm ZHANG Rong, LI Weiping, MO Tong. Review of deep learning[J]. Information and Control, 2018, 47(4): 385-397. https://www.cnki.com.cn/Article/CJFDTOTAL-XXYK201804002.htm
[5]	王文秀, 傅雨田, 董峰, 等. 基于深度卷积神经网络的红外船只目标检测方法[J]. 光学学报, 2018, 38(7): 0712006. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB201807020.htm WANG Wenxiu, FU Yutian, DONG Feng, et al. Infrared ship target detection method based on deep convolution neural network[J]. Acta Optica Sinica, 2018, 38(7): 0712006. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB201807020.htm
[6]	罗海波, 许凌云, 惠斌, 等. 基于深度学习的目标跟踪方法研究现状与展望[J]. 红外与激光工程, 2017, 46(5): 0502002-0502002(7). https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ201705002.htm LUO Haibo, XU Lingyun, HUI Bin, et al. Status and prospect of target tracking based on deep learning[J]. Infrared and Laser Engineering, 2017, 46(5): 0502002-0502002(7). https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ201705002.htm
[7]	Ross Girshick. Fast R-CNN[J]. Computer Science, 2015, 6: 1440-1448.
[8]	REN Shaoqing, HE Kaiming, Ross Girshick, et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2017, 39(6): 1137-1149.
[9]	HE Kaiming, Georgia Gkioxari, Piotr Dollar, et al. Mask R-CNN[C]// Proceedings of the IEEE Computer Society Conference on Computer Vision, 2017: 2961-2969.
[10]	LIU Wei, Dragomir Anguelov, Dumitru Erhan, et al. SSD: Single shot multibox detector[C]//European Conference on Computer Vision, 2016, 6: 21-27.
[11]	Joseph Redmon, Santosh Divvala, Ross Girshick, et al. You Only Look Once: unified, real-time object detection[C]//Conference on Computer Vision and Pattern Recognition, 2016, 6: 779-788.
[12]	Joseph Redmon, Ali Farhadi. YOLO9000: better, faster, stronger[C]// Conference on Computer Vision and Pattern Recognition, 2017, 7: 6517-6525
[13]	Joseph Redmon, Ali Farhadi. YOLOv3: an incremental improvement [J/OL]. arXiv: 1804.02767, 2018.
[14]	Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao. YOLOv4: optimal speed and accuracy of object detection[J/OL]. arXiv: 2004. 10934, 2020.
[15]	冈萨雷斯. 数字图像处理[M]. 第三版, 北京: 电子工业出版社, 2011: 26-29. Rafael C. Gonzalez. Digital Image Processing[M]. 3th, Beijing: Publishing House of Electronics Industry, 2011: 26-29.
[16]	Woo S, Park J, Lee J Y, et al. Cbam: Convolutional block attention module[C]//Proceedings of the European Conference on Computer Vision (ECCV). 2018: 3-19.
[17]	张汝榛, 张建林, 祁小平, 等. 复杂场景下的红外目标检测[J]. 光电工程, 2020, 47(10): 200314. https://www.cnki.com.cn/Article/CJFDTOTAL-GDGC202010010.htm ZHANG R Z, ZHANG J L, QI X P, et al. Infrared target detection and recognition in complex scene[J]. Opto-Electron Eng., 2020, 47(10): 200314. https://www.cnki.com.cn/Article/CJFDTOTAL-GDGC202010010.htm
[18]	宫剑, 吕俊伟, 刘亮, 等. 红外偏振图像的舰船目标检测[J]. 光谱学与光谱分析, 2020, 40(2): 586-594. https://www.cnki.com.cn/Article/CJFDTOTAL-GUAN202002052.htm GONG Jian, LYU Junwei, LIU Liang, et al. Ship target detection based on infrared polarization image[J]. Spectroscopy and Spectral Analysis, 2020, 40(2): 586-594. https://www.cnki.com.cn/Article/CJFDTOTAL-GUAN202002052.htm
[19]	游江, 刘鹏祖, 容晓龙, 等. 基于暗通道先验原理的偏振图像去雾增强算法研究[J]. 激光与红外, 2020, 50(4): 493-500. DOI: 10.3969/j.issn.1001-5078.2020.04.019 YOU Jiang, LIU Pengzu, RONG Xiaolong, et al. Dehazing and enhancement research of polarized image based on dark channel priori principle[J]. Laser & Infrared, 2020, 50(4): 493-500. DOI: 10.3969/j.issn.1001-5078.2020.04.019
[20]	王美荣, 徐国明, 袁宏武. 显著性偏振参量深度稀疏特征学习的目标检测方法[J]. 激光与光电子学进展, 2019, 56(19): 191101. https://www.cnki.com.cn/Article/CJFDTOTAL-JGDJ201919013.htm WANG Meirong, XU Guoming, YUAN Hongwu. Object detection by deep sparse feature learning of salient polarization parameters[J]. Laser & Optoelectronics Progress, 2019, 56(19): 191101. https://www.cnki.com.cn/Article/CJFDTOTAL-JGDJ201919013.htm
[21]	李慕锴, 张涛, 崔文楠. 基于YOLOv3的红外行人小目标检测技术研究[J]. 红外技术, 2020, 42(2): 176-181. http://hwjs.nvir.cn/article/id/hwjs202002012 LI Mukai, ZHANG Tao, CUI Wennan. Research of infrared small pedestrian target detection based on YOLOv3[J]. Infrared Technology, 2020, 42(2): 176-181. http://hwjs.nvir.cn/article/id/hwjs202002012

[1]	WANG Yefei, CHENG Yanping, YAO Yuan, LI Daojing, YU Xiao. Design of Membrane Diffractive Athermal Infrared Optical System[J]. Infrared Technology , 2021, 43(5): 422-428.
[2]	LI Shenghui, LI Xin, LI Hongjing. Design of Infrared Dual-Band Common Aperture Thermal Elimination Optical System Based on Harmonic Diffraction[J]. Infrared Technology , 2020, 42(1): 19-24.
[3]	HE Lei, ZHANG Jianlong, YANG Zhen, GUO Xinmin. Design of a Small Rolling-pitching Long-wave Infrared Optical System[J]. Infrared Technology , 2018, 40(12): 1142-1148.
[4]	LI Ruiyao, FU Yuegang, LIU Zhiying. Athermalization Design of Compact Medium-wave Infrared Imaging System[J]. Infrared Technology , 2018, 40(2): 119-124.
[6]	WU Guo-jun, BAI Ting-zhu, BAI Fu-ning. Research on Infrared Images Simulation by Inversing the Scene of the Visible Light Images[J]. Infrared Technology , 2011, 33(10): 574-579. DOI: 10.3969/j.issn.1001-8891.2011.10.004
[7]	WU Chun, LIU Xiang-xuan, WU You-peng. Study on the Preparation and Properties of Visible Light and Heat Infrared Camouflage Composite Materials[J]. Infrared Technology , 2009, 31(10): 602-606. DOI: 10.3969/j.issn.1001-8891.2009.10.011
[8]	BAI Yun, YANG Jian-feng, MA Xiao-long, XUE Bin, RUAN Ping, TIAN Hai-xia, WANG Hong-wei, LIANG Shi-tong, LI Xiang-juan. Athermalization of Long-wavelength Infrared Optical System[J]. Infrared Technology , 2008, 30(10): 583-585. DOI: 10.3969/j.issn.1001-8891.2008.10.007
[9]	CHEN Lv-ji, FENG Sheng-rong. A Compact Athermalizing Infrared Optical System[J]. Infrared Technology , 2007, 29(4): 203-205. DOI: 10.3969/j.issn.1001-8891.2007.04.004
[10]	MING Jing-qian, JIN Ning, GUO Lan, FENG Sheng-rong. An Athermal Design of Infrared Hybrid Refractive/Diffractive Optical System in 7.5~10.5μm Spectrum[J]. Infrared Technology , 2006, 28(5): 261-265. DOI: 10.3969/j.issn.1001-8891.2006.05.004

Cited By

Cited by

Periodical cited type(1)

周佳乐，宋敏敏，雷昊，刘建旭，曹卫卫，施瑶瑶，董大兴，刘友文. 基于YOLO与图像修复的仿真场景等效构设研究. 激光与红外. 2025(01): 145-154 .

Other cited types(1)

Get Citation

PDF

XML

Article views PDF downloads Cited by(2)

Multi-Target Detection of Low-Illuminance Scene Based on Polarization Image

Abstract

References

Related Articles

Cited by

Periodical cited type(1)

Other cited types(1)

Catalog

Related

Multi-Target Detection of Low-Illuminance Scene Based on Polarization Image

Abstract

References

Related Articles

Cited by

Periodical cited type(1)

Other cited types(1)

Catalog

Related

Export File

Citation

Format

Content