ISSN : 1796-203X
Volume : 3 Issue : 7 Date : July 2008
K-Cosine Corner Detection
Te-Hsiu Sun
Page(s): 16-22
Full Text: PDF (1,248 KB)
Abstract
This study presents a boundary-based corner detection method that achieves robust detection for
digital objects containing wide angles and various curves using curvature. The boundary of an
object is first represented into curvature measured by K-cosine. Then, by modifying the corner
detection error, this study proposes a suitable K value and curvature threshold for robust corner
detection. Furthermore, the proposed K-cosine corner detection (KCD) was verified with several
commonly employed digital objects. The experimental results reveal that the proposed method is
free from translation, rotation and scaling, and is superior to Tsai’s method [34] in computation
speed in discriminating false targets. A simple case study is shown finally to demonstrate the
feasibility and applicability for practical use of KCD.
Index Terms
K-cosine, corner detection, curvature, image processing
