A ROBUST CSS CORNER DETECTOR BASED ON THE TURNING ANGLE CURVATURE OF IMAGE GRADIENTS

TOPAL C., ÖZKAN K., BENLİGİRAY B., Akinlar C.

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Kanada, 26 - 31 Mayıs 2013, ss.1444-1448 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/icassp.2013.6637890
  • Basıldığı Şehir: Vancouver
  • Basıldığı Ülke: Kanada
  • Sayfa Sayıları: ss.1444-1448
  • Anahtar Kelimeler: Corner detection, curvature scale space (CSS), turning angle curvature, corner validation, SCALE-SPACE
  • Anadolu Üniversitesi Adresli: Evet

Özet

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.