Open AccessTwo-step skeletization of binary images based on the Zhang-Suen model and the producing mask
Author(s) -
Ц. Ма,
В. Ю. Цветков,
В. К. Конопелько
Publication year - 2021
Publication title -
sistemnyj analiz i prikladnaâ informatika
Language(s) - English
Resource type - Journals
eISSN - 2414-0481
pISSN - 2309-4923
DOI - 10.21122/2309-4923-2021-1-62-69
Subject(s) - skeletonization , pixel , artificial intelligence , noise (video) , binary image , image (mathematics) , mathematical morphology , computer science , pattern recognition (psychology) , computer vision , mathematics , binary number , position (finance) , medial axis , orientation (vector space) , algorithm , image processing , geometry , arithmetic , finance , economics
The aim of the work is to limit excessive thinning and increase the resistance to contour noise of skeletons resulted from arbitrary binary image shape while maintaining a high skeletonization rate. The skeleton is a set of thin lines, the relative position, the size and shape, which conveys information of size, shape and orientation in space of the corresponding homogeneous region of the image. To ensure resistance to contour noise, skeletonization algorithms are built on the basis of several steps. Zhang-Suen algorithm is widely known by high-quality skeletons and average performance, which disadvantages are the blurring of diagonal lines with a thickness of 2 pixels and the totally disappear patterns of 2x2 pixels. To overcome them, a mathematical model that compensates the Zhang-Suen algorithm has proposed in this paper, along with a producing mask and two logical conditions for evaluating its elements.