Edge Detection of Infrared Image Based on Morphology

doi:10.13190/j.jbupt.2020-109

Journal of Beijing University of Posts and Telecommunications ›› 2021, Vol. 44 ›› Issue (1): 66-71.doi: 10.13190/j.jbupt.2020-109

• PAPERS • Previous Articles Next Articles

Edge Detection of Infrared Image Based on Morphology

WANG Rui-nan¹, WU Mu-qing¹, CHEN Tie-ying², LI Zhi-gang², SUN Jian²

1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. Zhejiang Woosiyuan Communication Technology Company Limited, Hangzhou 310030, China

Received:2020-08-06 Online:2021-02-28 Published:2021-09-30

Abstract

Abstract: To improve the performance of infrared image edge detection,an edge detection algorithm based on morphology is proposed. This method improves the edge detection algorithm that only uses a single direction and fixed direction weights. It uses multi-directional structural elements to extract the edges of the image,and uses the direction adaptive weighted fusion method to obtain final results. Simulations show that the method can effectively suppress the noise in the image and make the extracted image edge more complete which improve the effect of infrared image edge detection.

Key words: edge detection, infrared image, morphology, adaptive weight

CLC Number:

TP391.41

WANG Rui-nan, WU Mu-qing, CHEN Tie-ying, LI Zhi-gang, SUN Jian. Edge Detection of Infrared Image Based on Morphology[J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(1): 66-71.

References

[1] 闫钧华, 段贺, 艾淑芳, 等. 旋转复杂背景中红外运动小目标实时检测[J]. 电子科技大学学报, 2017, 46(5):697-702. Yan Junhua, Duan He, Ai Shufang, et al. Real-Time detection for infrared motion small targets in rotation and complex background[J]. Journal of University of Electronic Science and Technology of China, 2017, 46(5):697-702.
[2] 匡平, 张明星, 万维. 基于尺度乘积的X射线焊缝区域提取算法研究[J]. 电子科技大学学报, 2015, 44(5):737-742. Kuang Ping, Zhang Mingxing, Wan Wei. Weld region extraction in radiographic image based on scale multiplication technique[J]. Journal of University of Electronic Science and Technology of China, 2015, 44(5):737-742.
[3] 荣婧, 潘玉利. 基于图像的水泥路面裂缝识别方法及应用[J]. 北京邮电大学学报, 2012, 35(6):121-124. Rong Jing, Pan Yuli. Image based crack detection algorithm with application to cement concrete pavament[J]. Journal of Beijing University of Posts and Telecommunications, 2012, 35(6):121-124.
[4] Poma X S, Riba E, Sappa A D. Dense extreme inception network:towards a robust CNN model for edge detection[C]//The IEEE Winter Conference on Applications of Computer Vision. Los Angeles:IEEE, 2020:1923-1932.
[5] Liu Yun, Cheng Mingming, Hu Xiaowei, et al. Richer convolutional features for edge detection[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. New York:IEEE, 2017:3000-3009.
[6] Deng Ruoxi, Shen Chunhua, Liu Shengjun, et al. Learning to predict crisp boundaries[C]//Proceedings of the European Conference on Computer Vision. Cham:Springer, 2018:562-578.
[7] 邓彩霞, 王贵彬, 杨鑫蕊. 改进的抗噪形态学边缘检测算法[J]. 数据采集与处理, 2013(6):47-53. Deng Caixia, Wang Guibin, Yang Xinrui. Improved algorithm of morphology in edge detection for noise resistance[J]. Journal of Data Acquisition and Processing, 2013(6):47-53.
[8] 胡志斌. 改进的二进小波与形态学融合的边缘检测算法[D]. 哈尔滨:哈尔滨理工大学, 2019:32-34.
[9] 韩璐. 改进的基于多尺度多方向结构元素和形态学的边缘检测算法[D]. 济南:山东大学, 2015:30-33.
[10] Ye Hanmin, Shen Bin, Yan Shili. Prewitt edge detection based on BM3D image denoising[C]//2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference. New York:IEEE, 2018:1593-1597.
[11] Zhang Yi, Han Xiaoyuan, Zhang Han, et al. Edge detection algorithm of image fusion based on improved Sobel operator[C]//2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference. New York:IEEE, 2017:457-461.

Edge Detection of Infrared Image Based on Morphology

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 5

Recommended Articles

Metrics

Comments

[1]	LI Hai-yan, WANG Wei-hua, GUO Lei, LI Hai-jiang, LI Hong-song. Two-Stage Network Inpainting Algorithm Based on BDCN and U-net Edge Generation [J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(5): 121-126.
[2]	PANG Zeng-zhi, SHI Jian-jie, YIN Jian-qin, ZHU Li-min, LI Jin-ping. Automatic Segmentation of Workpiece Based on Target Morphological Features [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(5): 119-126.
[3]	KOU Guang-jie, MA Yun-yan, YUE Jun. SAR Image Segmentation Based on SRADPRO and SCM Model [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2016, 39(1): 122-126.
[4]	Wen DING Qimei CHEN. A New Approach of Canny Edge Detection and Classification for Color Images [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2012, 35(1): 115-119.
[5]	. Exposing Digital Image Forgeries by Detecting Inconsistence in  Light Source Direction [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2011, 34(3): 26-30.