Scale-Based Detection of Corners of Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition Letters
Robust and Efficient Detection of Salient Convex Groups
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Image Corner Detection Through Curvature Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Curvature Scale Space Corner Detector with Adaptive Threshold and Dynamic Region of Support
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
A Corner-Finding Algorithm for Chain-Coded Curves
IEEE Transactions on Computers
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Corner detection is a main concern in many computer vision applications like object recognition or image matching. Furthermore, detection is usually performed over the contour of the objects. This paper presents a novel algorithm to detect corners based on CSS (curvature scale space). A multi-scale curvature polynomial is defined as the sum or product of the curvature under all scales of the contour. The new method can not only enhance curvature extreme peaks effectively, but also suppress noise and trivial details and prevent smoothing some corners with the augment of the scale. On the other hand, the detected corners belonging to the concave or convex can be judged by the result sign of the curvature polynomial. Experiment results show that the new method is more effective in corner detection than the other algorithms mentioned in the paper.