New Iterative Algorithms for Thinning Binary Images

Abstract

Thinning is a process of reducing an object in a digital image to the minimum size necessary for machine recognition of that object. Efficient and reliable thinning of image patterns is essential to a variety of applications in the field of image analysis and recognition system. In this paper we propose two new iterative algorithms for thinning binary images. In the first algorithm, thinning is accomplished by using two operations: edge detection and subtraction. Another algorithm is based on repeatedly conditionally eroding the pixels until a one pixel thick pattern is obtained. Erosion conditions are devised to assure preserving connectivity. Results of applying the algorithms on the variety of images will be shown. To judge performance of our algorithms, we made a comparison with some other major algorithm.