Introduction - If you have any usage issues, please Google them yourself
Difficult to see the classic Harris corner detection method, the algorithm stability and k, whereas k is an experience, not good grasp, floating there may be larger. In view of this, an improved method of Harris () directly calculates two characteristic values, by comparing two eigenvalues classification, so do not calculate the response function of Harris. On the other hand, we are no longer inhibited by non-maximum value, the distance tolerance: tolerance distance is only one feature point. Firstly, a point maximum and minimum eigenvalues have (ie: max (min (e1, e2)), e1, e2 is the characteristic value harris matrix) as the corners, followed in accordance with the maximum and minimum eigenvalues in order to find the remaining corner, of course, and the front corner of the distance in angular distance tolerate new point chanting ignored.