Analysis of gray level corner detection

Abstract In this paper the analysis of gray level corner detection has been carried out. Performances of various cornerness measures are discussed with respect to four performances of robustness: detection, localization, stability and complexity. We have analyzed the interior differential features of the image surface of these cornerness measures. This paper presents a new approach called gradient-direction corner detector for the corner detection which is developed from the popular Plessey corner detection. The gradient-direction corner detector is based on the measure of the gradient module of the image gradient direction and the constraints of the false corner response suppression.

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