A Comparative Analysis on Estimation of Fractal Dimension of Gray Scale Images
نویسندگان
چکیده
Fractal Dimension (FD) is an essential feature of fractal geometry that characterizes the surface roughness of complex or irritated objects. Though, fractal dimension gradually established its importance in the area of image processing by means of image segmentation, Pattern recognition, texture and medical signal analysis and many more. A number of algorithms for estimation of fractal dimension of images have been reported in many literatures. However different technique lead different result. The differential box counting is most popular and well liked technique in digital domain. In this paper, we have performed a comparative analysis among five different well liked techniques like differential box counting (DBC), relative DBC (RDBC), improved box counting (IBC), improved DBC (IDBC) and improved triangle box counting (ITBC) in terms of fitting error. The experimental work carried out by one set of sixteen brodatz database images and two set of generated synthetic texture like images. From this experimental result, we found by means of fitting error, IDBC performs the best among the five methods and solve simultaneously both over-counting and under-counting problems.
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