An Adaptive Threshold Corner Detector Based on Multi-scale Chord-Angle Sharpness Accumulation

We propose a new adaptive corner detector based on multi-scale chord-angle sharpness accu-mulation, which can reduce location error and detects fine accuracy on noisy images. Firstly, we use the canny detector to detect edges at low computational cost. Secondly, we devise support regions of the contour into three sections as scales and computes the chord-angel sharpness respectively, then accumulate the three scale sharpness as corner response function. Finally, we use an dynamic adaptive corner threshold to label corners. The results on fine and low quality images show that the proposed algorithm performs better than the other three algorithms in terms of both detection accuracy and location error.