DocumentCode :
2183793
Title :
Structural Feature Extraction from Regular-Shaped Rigid Objects(1) - Based on Gradient Direction Constraint Randomized Hough Transform
Author :
Zhang, Lei ; Fu, Qingshan ; Zhang, Xingguo ; Hua, Guoran ; Zhu, Longbiao
Author_Institution :
Sch. of the Mech. Eng., Nantong Univ., Nantong, China
Volume :
2
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
209
Lastpage :
214
Abstract :
The structural feature extraction from regular-shaped rigid objects is studied. First, some specific measures for facilitating the conventional Randomized Hough Transform (abbr. RHT) in our application are introduced. Then, a gradient direction constraint RHT is proposed for improving the poor performance of the conventional RHT that too much false response happens in noisy real images. The basic idea of the new method is that the edge points of the true straight edges have more consistent distribution of the gradient direction than the noise has. Last, experiments including subjective observations and quantitative statistics validate that the new approach has much more robust performance than the conventional RHT.
Keywords :
Hough transforms; edge detection; feature extraction; edge points; noisy real images; randomized Hough transform; regular-shaped rigid objects; structural feature extraction; Randomized Hough Transform; corner detection; feature extraction; straight line extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2010 International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-8094-4
Type :
conf
DOI :
10.1109/ISCID.2010.142
Filename :
5692771
Link To Document :
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