| Abstract: |
A more accurate algorithm for corner and edge detections that is the improved form of the well-known Harris’algorithm is introduced. First, instead of approximating |L[m+x, n+y]–L[m, n]|^2 just in terms of x^2, xy, and y^2, we will approximate |L[m+x, n+y]–L[m, n]|(L[m+x, n+y]–L[m, n]) by the linear combination of x^2, xy, y^2, x, y, and 1. With the modifications, we can observe the sign of variation. It can avoid misjudging the pixel at a dot or on a ridge as a corner and is also helpful for increasing the robustness to noise. Moreover, we also use orthogonal polynomial expansion and table looking up and define the cornity as the “integration” of the quadratic function to further improve the performance. From simulations, our algorithm can much reduce the probability of regarding a non-corner pixel as a corner. In addition, our algorithm is also effective for edge detection. |
