Real-Time Ship detection from Infrared Images Through Multi-feature Fusion

Rui Miao; Hongxu Jiang; Fangzheng Tian; Xiaobin Li; Yonghua Zhang; Dong Dong

doi:10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00079

Real-Time Ship detection from Infrared Images Through Multi-feature Fusion

Rui Miao
, Hongxu Jiang
, Fangzheng Tian
, Xiaobin Li
, Yonghua Zhang
, Dong Dong

School of Computer Science and Engineering

Beihang University

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

2 Scopus citations

Abstract

Real-time ship detection from remote sensing imagery it is a great challenge due to the complex scene, the changeable characteristics of ship target, and the uncontrollable interference factors. In this letter, an infrared ship detection algorithm based on multi-feature fusion is proposed. Based on the fully analysis of the target features, the proposed algorithm combines the cascade rejection mechanism with multi-features through a cascade linear classifier from simple to complex, and uses fine features to accurately distinguish the target from the complex background. Large number of experimental results show that the proposed method can achieve better results in detection performance and real-time processing.

Original language	English
Title of host publication	19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	533-538
Number of pages	6
ISBN (Electronic)	9781665435741
DOIs	https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00079
State	Published - 2021
Event	19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021 - New York, United States Duration: 30 Sep 2021 → 3 Oct 2021

Publication series

Name	19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021

Conference

Conference	19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021
Country/Territory	United States
City	New York
Period	30/09/21 → 3/10/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Image Processing
Multi-feature Fusion
Real-time

Access to Document

10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00079

Cite this

Miao, R., Jiang, H., Tian, F., Li, X., Zhang, Y., & Dong, D. (2021). Real-Time Ship detection from Infrared Images Through Multi-feature Fusion. In 19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021 (pp. 533-538). (19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00079

Miao, Rui ; Jiang, Hongxu ; Tian, Fangzheng et al. / Real-Time Ship detection from Infrared Images Through Multi-feature Fusion. 19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 533-538 (19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021).

@inproceedings{9b1478ef524a410aa541ecbaf8bece3c,

title = "Real-Time Ship detection from Infrared Images Through Multi-feature Fusion",

abstract = "Real-time ship detection from remote sensing imagery it is a great challenge due to the complex scene, the changeable characteristics of ship target, and the uncontrollable interference factors. In this letter, an infrared ship detection algorithm based on multi-feature fusion is proposed. Based on the fully analysis of the target features, the proposed algorithm combines the cascade rejection mechanism with multi-features through a cascade linear classifier from simple to complex, and uses fine features to accurately distinguish the target from the complex background. Large number of experimental results show that the proposed method can achieve better results in detection performance and real-time processing.",

keywords = "Image Processing, Multi-feature Fusion, Real-time",

author = "Rui Miao and Hongxu Jiang and Fangzheng Tian and Xiaobin Li and Yonghua Zhang and Dong Dong",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021 ; Conference date: 30-09-2021 Through 03-10-2021",

year = "2021",

doi = "10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00079",

language = "英语",

series = "19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "533--538",

booktitle = "19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021",

address = "美国",

}

Miao, R, Jiang, H, Tian, F, Li, X, Zhang, Y & Dong, D 2021, Real-Time Ship detection from Infrared Images Through Multi-feature Fusion. in 19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021. 19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021, Institute of Electrical and Electronics Engineers Inc., pp. 533-538, 19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021, New York, United States, 30/09/21. https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00079

Real-Time Ship detection from Infrared Images Through Multi-feature Fusion. / Miao, Rui; Jiang, Hongxu; Tian, Fangzheng et al.
19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 533-538 (19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021).

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

TY - GEN

T1 - Real-Time Ship detection from Infrared Images Through Multi-feature Fusion

AU - Miao, Rui

AU - Jiang, Hongxu

AU - Tian, Fangzheng

AU - Li, Xiaobin

AU - Zhang, Yonghua

AU - Dong, Dong

PY - 2021

Y1 - 2021

N2 - Real-time ship detection from remote sensing imagery it is a great challenge due to the complex scene, the changeable characteristics of ship target, and the uncontrollable interference factors. In this letter, an infrared ship detection algorithm based on multi-feature fusion is proposed. Based on the fully analysis of the target features, the proposed algorithm combines the cascade rejection mechanism with multi-features through a cascade linear classifier from simple to complex, and uses fine features to accurately distinguish the target from the complex background. Large number of experimental results show that the proposed method can achieve better results in detection performance and real-time processing.

AB - Real-time ship detection from remote sensing imagery it is a great challenge due to the complex scene, the changeable characteristics of ship target, and the uncontrollable interference factors. In this letter, an infrared ship detection algorithm based on multi-feature fusion is proposed. Based on the fully analysis of the target features, the proposed algorithm combines the cascade rejection mechanism with multi-features through a cascade linear classifier from simple to complex, and uses fine features to accurately distinguish the target from the complex background. Large number of experimental results show that the proposed method can achieve better results in detection performance and real-time processing.

KW - Image Processing

KW - Multi-feature Fusion

KW - Real-time

UR - https://www.scopus.com/pages/publications/85124144631

U2 - 10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00079

DO - 10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00079

M3 - 会议稿件

AN - SCOPUS:85124144631

T3 - 19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021

SP - 533

EP - 538

BT - 19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021

Y2 - 30 September 2021 through 3 October 2021

ER -

Miao R, Jiang H, Tian F, Li X, Zhang Y, Dong D. Real-Time Ship detection from Infrared Images Through Multi-feature Fusion. In 19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 533-538. (19th IEEE International Symposium on Parallel and Distributed Processing with Applications, 11th IEEE International Conference on Big Data and Cloud Computing, 14th IEEE International Conference on Social Computing and Networking and 11th IEEE International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2021). doi: 10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00079

Real-Time Ship detection from Infrared Images Through Multi-feature Fusion

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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