DocumentCode :
479791
Title :
Hough Transform Relative Nonuniform Parameter Space for the Detection of Line Segments
Author :
Min, Wang ; Yanning, Zhang
Volume :
1
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
764
Lastpage :
767
Abstract :
Linear feature detection is very important in computer vision, image segmentation and pattern recognition. The drawbacks of the standard Hough transform (SHT) are the quantization error and the location of line-segments. In this paper, the nonuniform quantization of HT parameter is proposed to decrease the influence the uniform quantization error of line-segments detection. Moreover, transforming HT parameter to relative parameter and decomposing the digital line to different scale line segments an increase the detection veracity. Experimental results are included to show that the proposed method can achieve high accuracy of line-segments detection and has robustness in the presence of noise.
Keywords :
Hough transforms; computer vision; edge detection; feature extraction; image segmentation; quantisation (signal); Hough transform; computer vision; edge detection; image segmentation; line segment detection; linear feature detection; parameter space; pattern recognition; uniform quantization error; Computer science; Computer vision; Digital images; Discrete transforms; Frequency; Image segmentation; Pixel; Quantization; Software engineering; Voting; Discrete image; Hough Transform; Line Segment; Mutiscale; Nonuniform quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.1376
Filename :
4721861
Link To Document :
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