Iterative segment approaching: new corner detection based on local response saliency
迭代分割逼近:新的基于局部响应显著度的角点检测

To improve detection accuracy and speed,a corner detection method based on the novel Local Corner Response Saliency(LCRS) and Iterative Segment Approaching(ISA) is proposed.First,a new metric,the Local Corner Response Saliency,is defined to measure the response saliency of a candidate corner point within the local region where it is located.The corner detection criterion based on LCRS proved to be equivalent to a local adaptive thresholding method.Then,by treating LCRS as a property of response saliency of a region,the task of searching corner points is transformed to the task of searching special regions with high saliency.With this point of view,an iterative segment strategy is suggested to gradually narrow down these salient regions and finally approaching the actual positions of the true corners.The ISA algorithm can work with various definition of corner response function(CRF),and its speed in average case is identical to the Harris detector.Experiments show that when using Noble’s CRF,the average false and miss detection rates of ISA are lower than those of Noble detector by 4.62% and 5.59%,respectively.When using the Harris’ CRF,these tow rates are also lower than those of the Harris detector by 2.87% and 3.37%,respectively.Moreover,in both cases the average running time of ISA is shorter than these of the Harris and Noble detectors.