Corner detector using invariant analysis

Corner detection has been shown to be very useful in many computer vision applications. Some valid approaches have been proposed, but few of them are accurate, efficient and suitable for complex applications (such as DSP). In this paper, a corner detector using invariant analysis is proposed. The new detector assumes an ideal corner of a gray level image should have a good corner structure which has an annulus mask. An invariant function was put forward, and the value of which for the ideal corner is a constant value. Then, we could verify the candidate corners by compare their invariant function value with the constant value. Experiments have shown that the new corner detector is accurate and efficient and could be used in some complex applications because of its simple calculation.

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