DocumentCode :
3485808
Title :
Applying multifractal spectrum combined with fractal discrete brownian motion model to wood defects recognition for sawing
Author :
Yu, Lei ; Qi, Dawei
Author_Institution :
Northeast Forestry Univ., Harbin, China
fYear :
2009
fDate :
5-7 Aug. 2009
Firstpage :
309
Lastpage :
314
Abstract :
Wood nondestructive testing technology is a new and comprehensive subject. In recent years it has achieved fast development. X-ray computed tomography (CT) scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to arrive at better wood sawing decision. Fractal geometry and its multifractal extension are new tools which can be used for describing, modeling, analyzing and processing different complex shapes and images. A method in CT image edge detection by using multifractal theory combined with fractal Brownian motion is applied in the paper. First its multifractal spectrum is estimated. Then different types of pixels are classified by the spectrum, smoothing edge point and singular edge point.
Keywords :
Brownian motion; computerised tomography; edge detection; image classification; nondestructive testing; sawing; spectral analysis; wood processing; X-ray computed tomography scanning technology; fractal discrete Brownian motion model; image edge detection; multifractal spectrum theory; sawing; smoothing edge point; wood defects recognition; wood nondestructive testing technology; Computed tomography; Fractals; Geometry; Image edge detection; Nondestructive testing; Sawing; Solid modeling; X-ray detection; X-ray detectors; X-ray imaging; Fractal Discrete Brownian Motion; Image segmentation; Multifractal spectrum; X-ray computed tomography; nondestructive testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-4794-7
Electronic_ISBN :
978-1-4244-4795-4
Type :
conf
DOI :
10.1109/ICAL.2009.5262908
Filename :
5262908
Link To Document :
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