Contour-based shape representation using principal curves

Esra Ataer-Cansizoglu, Erhan Bas, Jayashree Kalpathy-Cramer, Greg C. Sharp, Deniz Erdogmus

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Extraction and representation of contours are challenging problems and are crucial for many image processing applications. In this study, given a membership function that returns the score of a point belonging to a contour, we propose a method for contour representation based on the principal curve (PC) of this function. The proposed method provides a piecewise linear representation of the contour with fewer points while preserving shape. Varied experiments are conducted, including lung boundary representation in CT images and shape representation in handwritten images. The results show that the technique provides accurate shape representation.

Original languageEnglish (US)
Pages (from-to)1140-1150
Number of pages11
JournalPattern Recognition
Volume46
Issue number4
DOIs
Publication statusPublished - Apr 2013
Externally publishedYes

    Fingerprint

Keywords

  • Curve/contour matching
  • Shape representation and analysis

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Ataer-Cansizoglu, E., Bas, E., Kalpathy-Cramer, J., Sharp, G. C., & Erdogmus, D. (2013). Contour-based shape representation using principal curves. Pattern Recognition, 46(4), 1140-1150. https://doi.org/10.1016/j.patcog.2012.10.014