DocumentCode :
2940117
Title :
A PCNN-Based Edge Detection Algorithm for Rock Fracture Images
Author :
He, ChangTao ; Wang, Weixing
Author_Institution :
Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, ChengDu, China
fYear :
2010
fDate :
19-21 June 2010
Firstpage :
1
Lastpage :
4
Abstract :
Image segmentation has attracted the attention of researchers for many decades. Different approaches have been developed in order to find out the solution in many different segmentation situations. In this paper a novel method for rock fracture image using improved pulse coupled neural networks (PCNN) is presented. We apply progressive scan and region marked method to detect accurate edges of rock fracture images, the experiment results show that the proposed method can be used as a new image edge detection method. Compared to the traditional edge detection algorithms such as Canny operator and the other edge detection operators (e.g. vector gradient and MV), the proposed method can easily obtain the rock fracture images´ orientations, curvatures, lengths, apertures and other useful information.
Keywords :
edge detection; geophysical image processing; geophysical techniques; image segmentation; neural nets; rocks; Canny operator; PCNN-based edge detection algorithm; edge detection operators; image edge detection method; image segmentation; pulse coupled neural networks; region marked method; rock fracture image orientations; traditional edge detection algorithms; vector gradient; Artificial neural networks; Fires; Image edge detection; Image processing; Image segmentation; Joining processes; Mathematical model; Neural networks; Neurons; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Photonics and Optoelectronic (SOPO), 2010 Symposium on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4963-7
Electronic_ISBN :
978-1-4244-4964-4
Type :
conf
DOI :
10.1109/SOPO.2010.5504347
Filename :
5504347
Link To Document :
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