Scale-invariant Edge Detection Using Spectral Theory

Abstract

In this paper, we propose a method of scale-invariant edge detection that represents edge images as polynomials in a scale parameter using spectral decomposition (generalized PCA), in order to obtain an optimal local scale. As this proposed method is successfully able to estimate the local scale of each pixel, accurate scale-invariant edge amplitudes and directions can be obtained. Our experimental results show that the proposed method detects rough edge contours in indistinct parts and detailed contours in the clarified parts of test images.