Aircraft recognition based on convex-concave analysis

Xing Chao, Yanjun Li, Ke Zhang

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

1 Scopus citations

Abstract

The problem of aircraft recognition in a single image is analyzed. A novel method combined convex-concave feature and hierarchical analysis is introduced to do pattern recognition for aircraft using the feature of shapes and regions. Silhouettes obtained by image segmentation are described by chain code. Then convex-concave feature is computed from chaincode. Aircraft features are represented hierarchically with a sequence of convex-concave curves. Fast matching is performed with fundamental convex-concave feature, after which useful information (such as pose of the aircraft) can be obtained. The refined convex-concave feature is used to get detailed classification with additional information. Experimental results show the effectiveness of the algorithm for aircraft pose estimation in a gray level image.

Original languageEnglish
Title of host publicationProceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012
Pages1391-1395
Number of pages5
DOIs
StatePublished - 2012
Event2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012 - Chongqing, China
Duration: 29 May 201231 May 2012

Publication series

NameProceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012

Conference

Conference2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012
Country/TerritoryChina
CityChongqing
Period29/05/1231/05/12

Keywords

  • Mathematical morphological algorithm
  • Pose estimation
  • Radon transform

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