An Improved Differential Box Counting Method to Measure Fractal Dimensions for Pavement Surface Skid Resistance Evaluation

Measurement ◽  
2021 ◽  
pp. 109376
Author(s):  
Cheng Liu ◽  
You Zhan ◽  
Qiangsheng Deng ◽  
Yanjun Qiu ◽  
Allen Zhang
2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Youping Fan ◽  
Dai Zhang ◽  
Jingjiao Li

The paper aims to understand how the fractal dimension and growth time of electrical trees change with temperature and moisture. The fractal dimension of final electrical trees was estimated using 2-D box-counting method. Four groups of electrical trees were grown at variable moisture and temperature. The relation between growth time and fractal dimension of electrical trees were summarized. The results indicate the final electrical trees can have similar fractal dimensions via similar tree growth time at different combinations of moisture level and temperature conditions.


2011 ◽  
Vol 58-60 ◽  
pp. 1756-1761 ◽  
Author(s):  
Jie Xu ◽  
Giusepe Lacidogna

A fractal is a property of self-similarity, each small part of the fractal object is similar to the whole body. The traditional box-counting method (TBCM) to estimate fractal dimension can not reflect the self-similar property of the fractal and leads to two major problems, the border effect and noninteger values of box size. The modified box-counting method (MBCM), proposed in this study, not only eliminate the shortcomings of the TBCM, but also reflects the physical meaning about the self-similar of the fractal. The applications of MBCM shows a good estimation compared with the theoretical ones, which the biggest difference is smaller than 5%.


1998 ◽  
Vol 2 (2) ◽  
pp. 77-92 ◽  
Author(s):  
B. S. Daya Sagar ◽  
Charles Omoregie ◽  
B. S. Prakasa Rao

A fractal-skeletal based channel network (F-SCN) model is proposed. Four regular sided initiator-basins are transformed as second order fractal basins by following a specific generating mechanism with non-random rule. The morphological skeletons, hereafter referred to as channel networks, are extracted from these fractal basins. The morphometric and fractal relationships of these F-SCNs are shown. The fractal dimensions of these fractal basins, channel networks, and main channel lengths (computed through box counting method) are compared with those of estimated length–area measures. Certain morphometric order ratios to show fractal relations are also highlighted.


1992 ◽  
Vol 03 (02) ◽  
pp. 267-277 ◽  
Author(s):  
S. GOSHEN ◽  
R. THIEBERGER

An algorithm for calculating fractal dimensions by the box counting method is described. Parallel implementation of the algorithm is presented.


Fractals ◽  
2001 ◽  
Vol 09 (04) ◽  
pp. 403-414 ◽  
Author(s):  
R. SENGUPTA ◽  
N. DEY ◽  
DIPALI NAG ◽  
A. K. DATTA

Fractal behavior in the quasi-steady states of the two types of speech signals, namely, quasi-periodic and quasi-random, are studied. The signals of the first group consist of seven vowels and those for the second group consist of three variants each of three sibilants. Ten rendering of each of these signals by one native Bengali male speaker of 45 years of age are used as the signal database. Standard box-counting method is used for generating ln (pq) versus ln (1/r) curves. D0, Dq and the knee expanse (KE) of the curves, their interrelations and the projections on the source characteristics are the objects of analysis. D2>D0 is found to indicate locally dense nature of the map and are found to be associated mainly with some sibilants. Dq are found to be a family of simple polynomial functions of q for all signals. D0, Dq and KE are related to the nature of different signals and character of the sources generating the signals. The study of fractal dimensions and the generalized dimensions for these signals reveal intermittency behavior and multifractality, which indicate basically, turbulent source or sources for speech generation. That the quasi-periodic and the quasi-random sounds are fundamentally different is reflected in the behavior of generalized fractal dimensions.


Fractals ◽  
2012 ◽  
Vol 20 (03n04) ◽  
pp. 281-293 ◽  
Author(s):  
H. AHAMMER ◽  
M. MAYRHOFER-REINHARTSHUBER

The fractal dimensions of real world objects are commonly investigated using digital images. Unfortunately, these images are unable to represent an infinitesimal range of scales. In addition, a proper evaluation of the applied methods that encompass the image processing techniques is often missing. Several mathematical well-defined fractals with theoretically known fractal dimensions, represented by digital images, were investigated in this work. The very popular Box counting method was compared to a new image pyramid approach as well as to the Minkowski dilation method. Effects from noise and altered aspect ratios were also considered. The new Pyramid method is quite identical to the Box counting method, but it is easier to implement. Additionally, the calculation times are much shorter and memory requirements are almost comparable.


2014 ◽  
Vol 25 (5) ◽  
pp. 1102-1111 ◽  
Author(s):  
Yu Liu ◽  
Lingyu Chen ◽  
Heming Wang ◽  
Lanlan Jiang ◽  
Yi Zhang ◽  
...  

Fractals ◽  
2009 ◽  
Vol 17 (02) ◽  
pp. 171-180
Author(s):  
R. UTHAYAKUMAR ◽  
G. JAYALALITHA

In this paper we study a model of skin cancer (MM) in vitro, using geometry of fractals as the method of analysis. The fractal dimensions of moles (skin cancer cells) growth pattern have been measured by using the methods of Box-counting method (DB) and Sausage method (DS). The cell growth of this cancer can be modeled by Hidden Markov model (HMM) and percolation model which are depending upon the time complexity. From these models we can find the shape of the irregularity border by using the probability distribution of the cells. The variation in the irregular border of the skin cancer has been found out using ANOVA test and cell's compactness. The fractal approach led to very promising results which improved the determination and examination of the stage of skin cancer.


Fractals ◽  
2000 ◽  
Vol 08 (03) ◽  
pp. 261-265
Author(s):  
IAN H. PARKINSON ◽  
NIC L. FAZZALARI

Modified Richardson plots obtained by a box counting method on outlines of trabecular bone were tested for linearity. The degree of deviation from true linearity was quantified. The results showed that although there was evidence of nonlinearity or serial correlation in the Richardson plots, the magnitude of deviation from true linearity was less than 0.3% for the residuals and less than 4% for the standard deviation of the residuals. This study shows that the modified box counting method for estimating overall fractal dimension or sectional fractal dimensions of trabecular bone is efficacious. The low magnitude of deviation from linearity confirms that over a defined range of scale the Richardson plot provides an accurate estimation of the fractal dimension of trabecular bone.


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