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