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A Geometric Centroid Contour Distance for Scale/Rotation Robustness Using Shape Alignment and Feature Based Normalization

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Convergence and Hybrid Information Technology (ICHIT 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7425))

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Abstract

In this paper, we propose a Geometrical Centroid Contour Distance (GCCD) which is described by shape signature based on contour sequence. The proposed method uses geometrical relation features instead of the absolute angle based features after it was normalized and aligned with dominant feature of the shape. Experimental result with MPEG-7 CE-Shape-1 Data Set reveals that our method has low time/spatial complexity and scale/rotation robustness than the other methods, showing that the precision of our method is more accurate than the conventional descriptors. However, performance of the GCCD is limited with concave and complex shaped objects.

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© 2012 Springer-Verlag Berlin Heidelberg

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Song, HG., Koo, HS. (2012). A Geometric Centroid Contour Distance for Scale/Rotation Robustness Using Shape Alignment and Feature Based Normalization. In: Lee, G., Howard, D., Kang, J.J., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2012. Lecture Notes in Computer Science, vol 7425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32645-5_41

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  • DOI: https://doi.org/10.1007/978-3-642-32645-5_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32644-8

  • Online ISBN: 978-3-642-32645-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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