Corner detection based on evolution difference of plannar curves in Bspline scale space

In order to improve image corner detection precision and efficiency, a novel corner detection algorithm based on Bspline scale space evolution difference is proposed. The norm of DoB is defined as corner response function to evaluate the multiscale evolution difference. The DoB corner detector confluents the image boundary features with different scales, which can not only strengthen the response of the feature points, but also depress the influence of noise. Among all corner detection algorithms based on BSpline, the proposed algorithm is relatively lower for computation complexity and faster. The comparative experiments demonstrate that the proposed algorithm works well for localization, robustness against noise, as well as invariance to rotation and scalability.

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