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High-speed recognition algorithm based on BRISK and saliency detection for aerial images

  • Xiao Tengjiao*
  • , Zhao Danpei
  • , Shi Jun
  • , Lu Ming
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A fast ground object recognition method for aerial images, taking airports, oil depots, harbors etc. as research objects, is proposed in this paper based on BRISK and the visual saliency detection. According to the characteristics of aerial images, such as high resolution and complex background interference, saliency detection is applied to select the candidate object region where the target may exist. Therefore, it can reduce the searching range effectively. And then, BRISK matching method is used to recognize the object efficiently. A variety of experiments under different interference factors are carried out base on the typical object database of aerial images in this paper. Experimental results show that the proposed algorithm can not only maintain the validity of BRISK features under the conditions of rotation, scale, illumination and viewpoint changes, but also shorten the matching time, satisfying real-time demand.

Original languageEnglish
Title of host publicationProceedings of the 2013 3rd International Conference on Intelligent System Design and Engineering Applications, ISDEA 2013
Pages816-819
Number of pages4
DOIs
StatePublished - 2013
Event2013 3rd International Conference on Intelligent System Design and Engineering Applications, ISDEA 2013 - Hong Kong, China
Duration: 16 Jan 201318 Jan 2013

Publication series

NameProceedings of the 2013 3rd International Conference on Intelligent System Design and Engineering Applications, ISDEA 2013

Conference

Conference2013 3rd International Conference on Intelligent System Design and Engineering Applications, ISDEA 2013
Country/TerritoryChina
CityHong Kong
Period16/01/1318/01/13

Keywords

  • Aerial images
  • BRISK matching
  • Object recognition
  • Saliency detection

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