Skeleting of Low-Contrast Noisy Halftone Images

Abstract

The problem of forming the skeletons of halftone images with two-mode brightness histograms under conditions of changing contrast and noise is considered. On such histograms, one mode corresponds to the objects, and the other to the background. Thanks to this feature, images are relatively easy to binarize and then skeletonize. The skeleton of a region uniform in brightness is a set of thin (limited by one-pixel) connected lines enclosed within this region and compactly describing its structure. Under conditions of high contrast and low noise on the original halftone image, binary skeletonization algorithms are widely used. They are relatively simple and can be resistant to multiplicative noise that appears at the boundaries of the regions after binarization. However, when the contrast is reduced and the noise of the original halftone image is increased, the skeletons formed by such algorithms are destroyed under the influence of additive noise, which manifests itself in the depth of the regions of the skeletonized binary image. To reduce skeletonization errors in such cases, algorithms based on preliminary low-pass filtering of the original grayscale image are used. To increase the stability of the skeletons of halftone images with a two-mode brightness histogram to noise, the article proposes a skeletonization model that takes into account the presence of multiplicative and additive noise components in a binary skeletonized image. Taking this model into account, a skeletonization algorithm has been developed, which takes into account the distortions in the shapes of the areas of the skeletonized binary image as a result of low-frequency filtering of the original halftone image and allows to reduce errors in the skeletonization of halftone images.