A Systematic Scheme for Automatic Airplane Detection from High-Resolution Remote Sensing Images

Jiao Zhao, Jing Han, Chen Feng, Jian Yao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Airport and airplane are typical objects in remote sensing research field. However, there are rare methods to detect airport and airplane in a unit system. In this paper, we propose a systematic scheme for airport detection and airplane detection from high-resolution remote sensing images. The airport detection part is mainly based on the parallel line features of runway, containing six main stages: down-sampling, Frequency-Tuned (FT) saliency detection, Line Segment Detector (LSD) line detection, line growing, parallel lines detection and line clustering. The airplane detection part is mainly based on Circle Frequency Filter (CF-filter) and a Fast R-CNN deep learning model. Experimental results on 500 high-resolution remote sensing images acquired more than 95% accuracy, and the average detection time was about 14 s, which proved that the proposed system was effective and efficient.

Original languageEnglish (US)
Title of host publicationImage and Video Technology - PSIVT 2017 International Workshops, Revised Selected Papers
EditorsShin’ichi Satoh
PublisherSpringer-Verlag
Pages465-478
Number of pages14
ISBN (Print)9783319927527
DOIs
StatePublished - Jan 1 2018
Event8th Pacific Rim Symposium on Image and Video Technology, PSIVT 2017 - Wuhan, China
Duration: Nov 20 2017Nov 24 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10799 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th Pacific Rim Symposium on Image and Video Technology, PSIVT 2017
CountryChina
CityWuhan
Period11/20/1711/24/17

Fingerprint

Remote Sensing Image
Airports
Remote sensing
High Resolution
Aircraft
Line Detection
Line
Saliency
Sampling
Line segment
Detectors
Remote Sensing
Circle
Detector
Clustering
Filter
Unit
Experimental Results

Keywords

  • Airplane detection
  • Circle Frequency Filter
  • Deep learning
  • High-resolution remote sensing images

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Zhao, J., Han, J., Feng, C., & Yao, J. (2018). A Systematic Scheme for Automatic Airplane Detection from High-Resolution Remote Sensing Images. In S. Satoh (Ed.), Image and Video Technology - PSIVT 2017 International Workshops, Revised Selected Papers (pp. 465-478). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10799 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-319-92753-4_36

A Systematic Scheme for Automatic Airplane Detection from High-Resolution Remote Sensing Images. / Zhao, Jiao; Han, Jing; Feng, Chen; Yao, Jian.

Image and Video Technology - PSIVT 2017 International Workshops, Revised Selected Papers. ed. / Shin’ichi Satoh. Springer-Verlag, 2018. p. 465-478 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10799 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhao, J, Han, J, Feng, C & Yao, J 2018, A Systematic Scheme for Automatic Airplane Detection from High-Resolution Remote Sensing Images. in S Satoh (ed.), Image and Video Technology - PSIVT 2017 International Workshops, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10799 LNCS, Springer-Verlag, pp. 465-478, 8th Pacific Rim Symposium on Image and Video Technology, PSIVT 2017, Wuhan, China, 11/20/17. https://doi.org/10.1007/978-3-319-92753-4_36
Zhao J, Han J, Feng C, Yao J. A Systematic Scheme for Automatic Airplane Detection from High-Resolution Remote Sensing Images. In Satoh S, editor, Image and Video Technology - PSIVT 2017 International Workshops, Revised Selected Papers. Springer-Verlag. 2018. p. 465-478. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-92753-4_36
Zhao, Jiao ; Han, Jing ; Feng, Chen ; Yao, Jian. / A Systematic Scheme for Automatic Airplane Detection from High-Resolution Remote Sensing Images. Image and Video Technology - PSIVT 2017 International Workshops, Revised Selected Papers. editor / Shin’ichi Satoh. Springer-Verlag, 2018. pp. 465-478 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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