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Algorithms of Image Line Feature Extraction Using Beamlet Transform

Author: ShaoFang
Tutor: ShuiPengLang
School: Xi'an University of Electronic Science and Technology
Course: Computational Mathematics
Keywords: Beamlet transform Line Feature Extraction Canny operator Any window
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 187
Quote: 3
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Abstract


Beamlet transformation is one of the effective tools for image multiscale geometric analysis . The basic theory of this article from continuous Beamlet transform the start, analysis Extraction Beamlet transform the online features of the application . Role the segment position Beamlet analysis equivalent point in the wavelet analysis , wavelet scale of the local region of space , position represented , while a representation of the local scale , location and orientation of the Beamlet can provide based on the organization of the binary segment . Line features based on Beamlet the pyramid extract including structure , tree structure , line segments local chain and segments the global chain algorithm . This paper studies the image line based on Beamlet transform feature extraction algorithm . First proposed based on Canny operator and Beamlet image line feature extraction method . First use Beamlet to extract line features , use Canny operator to remove the false edges . The experimental results demonstrate the effectiveness of this method . The paper also raises A arbitrary window Beamlet transform image line feature extraction method . First, the window of arbitrary shape , smoothing the noise , and further integration into a binary image , and then , re-use Beamlet extracted image line characteristic . It not only can extract linear features , but also to efficiently extract the curve characteristics . The experimental results show that in the case of SNR low , satisfactory results can be obtained with this method .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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