A robust CSS corner detector based on the turning angle curvature of image gradients

Topal C., ÖZKAN K., Benligiray B., AKINLAR C.

2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013, Vancouver, Canada, 26 - 31 May 2013, pp.1444-1448 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icassp.2013.6637890
  • City: Vancouver
  • Country: Canada
  • Page Numbers: pp.1444-1448
  • Keywords: Corner detection, corner validation, curvature scale space (CSS), turning angle curvature
  • Istanbul Technical University Affiliated: Yes


In this study, we present a new contour-based corner detection method based on the turning angle curvature computed from the contour gradients of the image. In general, curvature is computed with the pixel locations of the extracted image contours. In most contour extraction methods, the image gradient information is already computed. The proposed algorithm makes use of this available information to compute the curvature function and takes local extremums as potential corner candidates. Afterwards, the candidates are validated by a novel validation algorithm which tries to approximate the local geometric structure of the contour with an iterative least squares estimation algorithm. Thus, we not only eliminate the false detected corners; but also estimate the corner strength precisely in terms of degrees. The experiments show that the detected corners with gradient-based turning angle curvature are more durable to affine transformations according to the ACU and LE criterions. © 2013 IEEE.