scholarly journals Image Processing in Biology Based on the Fractal Analysis

10.5772/7059 ◽  
2009 ◽  
Author(s):  
Istvn Sztojnov ◽  
Daniela Alexandra ◽  
Ctlina Popescu ◽  
Vasilic Voine
Keyword(s):  
Image Processing ◽  
Fractal Analysis

Specimen preparation for high contrast image processing and fractal analysis of branching fungal colonies

1994 ◽  
Vol 8 (5) ◽  
pp. 313-318 ◽  
Author(s):  
Cameron L. Jones ◽  
Greg T. Lonergan ◽  
David E. Mainwaring
Keyword(s):  
Image Processing ◽  
Fractal Analysis ◽  
Specimen Preparation ◽  
High Contrast ◽  
Contrast Image

Fractal analysis of the retrogradation of rice starch by digital image processing

2012 ◽  
Vol 109 (1) ◽  
pp. 182-187 ◽  
Author(s):  
Yue Wu ◽  
Qinlu Lin ◽  
Zhengxing Chen ◽  
Wei Wu ◽  
Huaxi Xiao
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Fractal Analysis ◽  
Rice Starch

scholarly journals Fractal Analysis of Laplacian Pyramidal Filters Applied to Segmentation of Soil Images

2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
J. de Castro ◽  
F. Ballesteros ◽  
A. Méndez ◽  
A. M. Tarquis
Keyword(s):  
Image Processing ◽  
Fractal Analysis ◽  
Classical Problem ◽  
Basis Functions ◽  
Test Results ◽  
Threshold Values ◽  
Laplacian Pyramid ◽  
Reliable Test ◽  
Local Operators ◽  
Fractal Filters

The laplacian pyramid is a well-known technique for image processing in which local operators of many scales, but identical shape, serve as the basis functions. The required properties to the pyramidal filter produce a family of filters, which is unipara metrical in the case of the classical problem, when the length of the filter is 5. We pay attention to gaussian and fractal behaviour of these basis functions (or filters), and we determine the gaussian and fractal ranges in the case of single parametera. These fractal filters loose less energy in every step of the laplacian pyramid, and we apply this property to get threshold values for segmenting soil images, and then evaluate their porosity. Also, we evaluate our results by comparing them with the Otsu algorithm threshold values, and conclude that our algorithm produce reliable test results.

Fractal analysis of eroded surfaces by digital image processing

2002 ◽  
Vol 56 (4) ◽  
pp. 512-517 ◽  
Author(s):  
Luciano M.F Ribeiro ◽  
Ana Lucia Horovistiz ◽  
Glaucio A Jesuı́no ◽  
Luis Rogerio de O Hein ◽  
Noelmar P Abbade ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Fractal Analysis
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