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Recognition of Partially Occluded Binary Objects using Elastic Deformation Energy Measure

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2014, 19(10), pp.63-70
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

문영인 1 KOO JA YOUNG 1

1단국대학교

Accredited

ABSTRACT

Process of recognizing objects in binary images consists of image segmentation and pattern matching. If binary objects in the image are assumed to be separated, global features such as area, length ofperimeter, or the ratio of the two can be used to recognize the objects in the image. However, if such anassumption is not valid, the global features can not be used but local features such as points or line segments should be used to recognize the objects. In this paper points with large curvature along theperimeter are chosen to be the feature points, and pairs of points selected from them are used as localfeatures. Similarity of two local features are defined using elastic deformation energy for making thelengths and angles between gradient vectors at the end points same. Neighbour support value is definedand used for robust recognition of partially occluded binary objects. An experiment on Kimia-25 datashowed that the proposed algorithm runs 4.5 times faster than the maximum clique algorithm with samerecognition rate.

Citation status

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