scholarly journals Determination of the Fractal Dimension of the Fracture Network System Using Image Processing Technique

2019 ◽  
Vol 3 (2) ◽  
pp. 17 ◽  
Author(s):  
Rouhollah Basirat ◽  
Kamran Goshtasbi ◽  
Morteza Ahmadi

Fractal dimension (FD) is a critical parameter in the characterization of a rock fracture network system. This parameter represents the distribution pattern of fractures in rock media. Moreover, it can be used for the modeling of fracture networks when the spatial distribution of fractures is described by the distribution of power law. The main objective of this research is to propose an automatic method to determine the rock mass FD in MATLAB using digital image processing techniques. This method not only accelerates analysis and reduces human error, but also eliminates the access limitation to a rock face. In the proposed method, the intensity of image brightness is corrected using the histogram equalization process and applying smoothing filters to the image followed by revealing the edges using the Canny edge detection algorithm. In the next step, FD is calculated in the program using the box-counting method, which is applied randomly to the pixels detected as fractures. This algorithm was implemented in different geological images to calculate their FDs. The FD of the images was determined using a simple Canny edge detection algorithm, a manual calculation method, and an indirect approach based on spectral decay rate. The results showed that the proposed method is a reliable and fast approach for calculating FD in fractured geological media.

2020 ◽  
Vol 8 (5) ◽  
pp. 1656-1660

For any image identification based applications, edge detection is the primary step. The intention of the edge detection in image processing is to minimize the information that is not required in the analysis of identification of an image. In the process of reduction of insignificant data in the image, it may lead to some loss in information which in turn raise some problems like missing of boundaries with low contrast, false edge detection and some other noise affected problems. In order to reduce the effects due to noise, a modified version of popular edge detection algorithm “Canny edge detection algorithm” is proposed. Artix 7 FPGA board set up is used to implement, by using Xilinx platform the image that is obtained as output is displayed on monitor which is connected with FPGA board using connector port DVI. MATLAB Simulink is used for algorithm simulation and then it is executed on FPGA board using Xilinx platform. The results provide good motivation to use in different edge detection applications.


Author(s):  
Eric Clark ◽  
Gabriel Hotchner ◽  
Ebin Scaria ◽  
Ebin Scaria

The capability to detect edges in an image is a major component in the field of image processing. That being said one of the most commonly utilized methods for edge detection is the Canny edge detection algorithm. In this paper we outline and define what edge detection is in image processing, and how the Canny edge detector works in typical implementations. We briefly refer to other papers which have similarly looked into optimizing the Canny edge detector and then propose our own hypothesis on how to parallelize this algorithm via multithreading. Our current code implementation is then explained alongside current results and issues.


Author(s):  
Eric Clark ◽  
Gabriel Hotchner ◽  
Ebin Scaria

The capability to detect edges in an image is a major component in the field of image processing. That being said one of the most commonly utilized methods for edge detection is the Canny edge detection algorithm. In this paper we outline and define what edge detection is in image processing, and how the Canny edge detector works in typical implementations. We briefly refer to other papers which have similarly looked into optimizing the Canny edge detector and then propose our own hypothesis on how to parallelize this algorithm via multithreading. Our current code implementation is then explained alongside current results and issues. \\\\Keywords-Canny Edge detection, parallel, multithreading, Robot Vision, image processing.


2012 ◽  
Vol 220-223 ◽  
pp. 1279-1283 ◽  
Author(s):  
Li Hong Dong ◽  
Peng Bing Zhao

The coal-rock interface recognition is one of the critical automated technologies in the fully mechanized mining face. The poor working conditions underground result in the seriously polluted edge information of the coal-rock interface, which affects the positioning precision of the shearer drum. The Gaussian filter parameters and the high-low thresholds are difficult to select in the traditional Canny algorithm, which causes the information loss of gradual edge and the phenomenon of false edge. Consequently, this paper presents an improved Canny edge detection algorithm, which adopts the adaptive median filtering algorithm to calculate the thresholds of Canny algorithm according to the grayscale mean and variance mean. This algorithm can protect the image edge details better and can restrain the blurred image edge. Experimental results show that this algorithm has improved the edge extraction effect under the case of noise interference and improved the detection precision and accuracy of the coal-rock image effectively.


2019 ◽  
Vol 13 (2) ◽  
pp. 133-144 ◽  
Author(s):  
Dini Sundani ◽  
◽  
Sigit Widiyanto ◽  
Yuli Karyanti ◽  
Dini Tri Wardani ◽  
...  

2020 ◽  
Vol 33 (03) ◽  
Author(s):  
AMALAPURAPU SRINAG ◽  
◽  
M RABBANI ◽  
P ASHOK BABU ◽  
◽  
...  

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