Using The Generalized Radon Transform For Detection Of Curves In Noisy Images

Abstract

In this paper the discrete generalized Radon transform will be investigated as a tool for detection of curves in noisy digital images. The discrete generalized Radon transform maps an image into a parameter domain, where curves following a specific parameterized curve form will correspond to a peak in the parameter domain. A major advantage of the generalized Radon transform is that the curves are allowed to intersect. This enables a thresholding algorithm in the parameter domain for simultaneous detection of curve parameters. A threshold level based on the noise level in the image is derived. A numerical example is presented to illustrate the theory. 1. INTRODUCTION In recent years the Hough transform [1] and the related Radon transform [2] have received much attention. These two transforms are able to transform two dimensional images with lines into a domain of possible line parameters, where each line in the image will give a peak positioned at the corresponding line parameters. T..