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Trabecular Bone Texture Characterization Using Regularization Dimension and Box-counting Dimension
TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON), 2019This paper presents texture characterization techniques for effective diagnosis of osteoporosis cases on bone radiograph images. The automatic classification of osteoporosis and healthy (control) cases with bone radiograph images presents a major challenge as the images show little or no visual difference for both cases.
Dhevendra Alagan Palanivel +3 more
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A New Box-Counting Method for Estimation of Image Fractal Dimension
2006 International Conference on Image Processing, 2006Fractal dimension (FD) is an effective measure for complex objects. It is widely applied in the fields of image segmentation and shape recognition. This paper presents a new box-counting method for estimation of fractal dimension of images. Original ideas of the method came from the principles of differential box-counting (DBC) method.
Jian Li, Caixin Sun, Qian Du 0001
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A box-counting fractal dimension for feature extraction in iris recognition
2011 International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS), 2011Iris recognition is one of a popular Biometrics technique for identifying people. Normally, iris color and texture have been created since the first three months and they will be completed within one year. Iris will then remain unchanged until the end of one's life. Both sides of the iris eyes are different. Moreover, the iris is unique and independent
Atikarn Kraitong +2 more
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Box-Counting Dimension of Fractal Urban Form
International Journal of Artificial Life Research, 2012The difficulty to obtain a stable estimate of fractal dimension for stochastic fractal (e.g., urban form) is an unsolved issue in fractal analysis. The widely used box-counting method has three main issues: 1) ambiguities in setting up a proper box cover of the object of interest; 2) problems of limited data points for box sizes; 3) difficulty in ...
Shiguo Jiang, Desheng Liu
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The box-counting dimension for geometrically finite Kleinian groups
Fundamenta Mathematicae, 1996Patterson was the first studying the limit set in terms of measure theory and in particular, in terms of fractal dimensions. By constructing a measure, later called Patterson measure, on the limit set, he was able to get the following result for a finitely generated Fuchsian group \(G\): ``The exponent of convergence \(\gamma=\delta(G)\) is equal to \(\
Stratmann, B., Urbański, M.
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Hausdorff dimension method reduces the error of box counting
Theoretical and Natural Science, 2023The Hausdorff dimension of an object is a topological measure of the size of its covering properties. To compute the Hausdorff dimension of an object, this report reviews the method of box counting, a method of gathering data for analyzing complex patterns by breaking a dataset, object, image, etc.
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The Hausdorff and box-counting dimensions of a class of recurrent sets
Chaos, Solitons & Fractals, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dai, Meifeng, Liu, Xi
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How to get the reliable fractal dimension by the box counting
Communications in Nonlinear Science and Numerical Simulation, 1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yun Huang, Ying Gu, Sheng Wang
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An efficient procedure to compute fractal dimensions by box counting
Physics Letters A, 1986Abstract We consider the problem of computing fractal dimensions by the box-counting method. First, we remark that the computations can be performed efficiently with the technique of virtual memory so that large memories can be dealt with. Secondly, we use a scaling law which allows to avoid large numbers of iterations.
A. Giorgilli +3 more
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Coarse iris classification using box-counting to estimate fractal dimensions
Pattern Recognition, 2005This paper proposes a novel algorithm for the automatic coarse classification of iris images using a box-counting method to estimate the fractal dimensions of the iris. First, the iris image is segmented into sixteen blocks, eight belonging to an upper group and eight to a lower group. We then calculate the fractal dimension value of these image blocks
Li Yu +3 more
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