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A Computational-Geometry Approach to Digital Image Contour Extraction

  • Minghui Jiang
  • Xiaojun Qi
  • Pedro J. Tejada
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6750)

Abstract

We present a simple method based on computational-geometry for extracting contours from digital images. Unlike traditional image processing methods, our proposed method first extracts a set of oriented feature points from the input images, then applies a sequence of geometric techniques, including clustering, linking, and simplification, to find contours among these points. Extensive experimental results on synthetic and natural images show that our method can effectively extract contours from both clean and noisy images. Experiments on the Berkeley Segmentation Dataset also show that our proposed computational-geometry method can be linked with any state-of-the-art pixel-based contour extraction algorithm to remove noise and close gaps without severely dropping the contour accuracy. Moreover, contours extracted by our method have a much more compact representation than contours obtained by traditional pixel-based methods. Such a compact representation allows more efficient extraction of shape features in subsequent computer vision and pattern recognition tasks.

Keywords

contour extraction image processing computational geometry point linking 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Minghui Jiang
    • 1
  • Xiaojun Qi
    • 1
  • Pedro J. Tejada
    • 1
  1. 1.Department of Computer ScienceUtah State UniversityLoganUSA

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