An Improved Method for Corner Detection Based on Arcs
Yanqiu Wu · Computer Engineering and Science · 2011
In view of that the traditional image corner detection algorithm accuracy is not high and the speed is low,we propose a fast and novel corner detection algorithm with high precision.The difference between our algorithm and the traditional ones is that the USAN area corresponding to the arc and the corner pixel gray similarity to complete the extraction corner are taken into consideration.Thus,the computational cost is largely reduced and the detection precision as well as other performances are well guaranteed.Considering the issue of the fixed threshold,we adopt a new method that can select the threshold automatically.The proposed method is compared with the SUSAN and CSS corner detectors in accuracy rate,missing detection and precision,and so on.The results show that our algorithm has good performance for both synthesized and real images.