DocumentCode :
304582
Title :
A nonparametric approach for detecting lines and curves
Author :
Lim, Gek ; Alder, Michael
Author_Institution :
Centre for Intelligent Inf. Process. Syst., Western Australia Univ., Nedlands, WA, Australia
Volume :
1
fYear :
1996
fDate :
16-19 Sep 1996
Firstpage :
837
Abstract :
The process of detecting lines and curves in an image is an important component of many pattern recognition and computer vision applications. There are well understood approaches to finding curves from a parametrised space of curves. In many practical cases, however, there exist arbitrary shape curves, and different types of curves in the same image. In addition, local perturbation noise can be added to the images. We propose a nonparametric method to overcome the above mentioned problems. The method is based on local modeling of the data. It does not require the specification of a parametric space of curves. It can be used to detect arbitrary curves and thus has a wider applicability than parametric approaches
Keywords :
computer vision; edge detection; arbitrary shape curves; computer vision; curves detection; image processing; lines detection; local modeling; local perturbation noise; nonparametric approach; pattern recognition; Application software; Australia; Clustering algorithms; Computer vision; Information processing; Intelligent systems; Noise shaping; Pattern recognition; Pixel; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
Type :
conf
DOI :
10.1109/ICIP.1996.559629
Filename :
559629
Link To Document :
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