DocumentCode
2007490
Title
A Method for Nondestructive Testing of Wood Defects Based on Fractional Brownian Motion
Author
Li, Li ; Qi, Dawei ; Song, Jingwei ; Mu, Hongbo
Author_Institution
Northeast Forestry Univ., Harbin
fYear
2007
fDate
May 30 2007-June 1 2007
Firstpage
2021
Lastpage
2026
Abstract
Applying the fractional Brownian motion model, we investigate and analyze fractal dimension of the x-ray image of wood with hollow heart. Firstly, pre-process the wood image so that the image features are enhanced and more suitable for later processing. Then derive fractal dimension estimation algorithm based on the fractional Brownian motion model and calculate fractal dimensions of all the sub areas in wood image one by one. The results show that the fractal dimensions in the normal regions are higher than that of the edges. We can extract the edges of wood defects effectively according to this rule. It can be known from the experimental results that this method is effective for testing inner defects of wood, and has important significance for promoting the application of fractal theory. At the same time this study provides a new method for digital image processing and edge detection.
Keywords
Brownian motion; X-ray imaging; edge detection; feature extraction; fractals; nondestructive testing; wood; digital X-ray image processing; edge detection; feature extraction; fractal dimension analysis; fractal dimension estimation algorithm; fractional Brownian motion; hollow heart; nondestructive wood defect testing; Brownian motion; Digital images; Fractals; Heart; Image analysis; Image edge detection; Image motion analysis; Motion estimation; Nondestructive testing; X-ray imaging; Hurst exponent; fractal dimension; fractional Brownian motion; wood nondestructive testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-1-4244-0818-4
Electronic_ISBN
978-1-4244-0818-4
Type
conf
DOI
10.1109/ICCA.2007.4376715
Filename
4376715
Link To Document