An Efficient Box-Couting Fractal Dimension Approach for Experimental Image Variation Characterization

摘要

Many applications of fractal concepts rely on the ability to estimate the fractal dimension (FD) of objects. FD is a attempt to quantify how densely a fractal occupies the space in which it lies. This characteristic has been used in texture classification, segmentation and other problems. An efficient algorithm to estimate FD of images is proposed in this paper. We suggest its use to identify on line image deviation froma standard pattern. We report on some experiments on textile failings and comparison with four other methods.