K-Cosine Corner Detection

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.

• Type: Journal
• Year: 2008
• Where: JCP
• Authors: Te-Hsiu Sun
• Keywords: Boundary-based Corner Detection, Corner Detection, Corner Detection Error, JCP 2006, JCP 2008