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Synthetic Vision Assisted Real-Time Runway Detection for Infrared Aerial Images

  • Changjiang Liu
  • Irene Cheng
  • Anup Basu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11010)

Abstract

This paper presents a new real-time runway detection based on synthetic vision and level set method. It mainly focuses on the initial level set function and time performance. As for the initial level set function, three-thresholding segmentation is derived to obtain the subset of the runway, which serves as an initial curve to induce the initial level set function. As for time performance, a ROI (Region of Interest) based evolution method is proposed. Analysis of experimental results and comparisons with existing algorithms demonstrate the efficiency and accuracy of the proposed method.

Keywords

ROI propagation Three-thresholding Segmentation Synthetic vision Level set method 

Notes

Acknowledgment

The work was supported in part by the Open Project of the Key Lab of Enterprise Informationization and Internet of Things of Sichuan Province under Grant No. 2017WZY01, Natural Science Foundation of Sichuan University of Science and Engineering (SUSE) under Grant Nos. 2015RC08, 2017RCL54 and JG-1707. The authors would like to thank National Natural Science Foundation of China under Grant No. 11705122, NSERC, Canada, for their financial support of this research.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Key Lab of Enterprise Informationization and Internet of Things of Sichuan ProvinceSichuan University of Science and EngineeringZigongChina
  2. 2.Department of Computing ScienceUniversity of AlbertaEdmontonCanada

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