Bilateral Symmetry Detection on the Basis of Scale Invariant Feature Transform

Habib Akbar, Khizar Hayat, Nuhman ul Haq and Usama Ijaz Bajwa

PLOS ONE, 2014, vol. 9, issue 8, 1-8

Abstract: The automatic detection of bilateral symmetry is a challenging task in computer vision and pattern recognition. This paper presents an approach for the detection of bilateral symmetry in digital single object images. Our method relies on the extraction of Scale Invariant Feature Transform (SIFT) based feature points, which serves as the basis for the ascertainment of the centroid of the object; the latter being the origin under the Cartesian coordinate system to be converted to the polar coordinate system in order to facilitate the selection symmetric coordinate pairs. This is followed by comparing the gradient magnitude and orientation of the corresponding points to evaluate the amount of symmetry exhibited by each pair of points. The experimental results show that our approach draw the symmetry line accurately, provided that the observed centroid point is true.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0103561

DOI: 10.1371/journal.pone.0103561

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