DocumentCode
2607668
Title
Sub-pixel Edge Detection Based on Curve Fitting
Author
Xu Guo-sheng
Author_Institution
Weifang Univ., Weifang, China
Volume
2
fYear
2009
fDate
21-22 May 2009
Firstpage
373
Lastpage
375
Abstract
Aimed at the problem that it s difficult to improve the identify precision of the linear CCD scan image, a novel fast sub-pixel edge detection method for image measurement is proposed. According to the step jump characteristic of the image edge gray degree and grads, it can determine the pixel boundary of the CCD image through edge automatic detecting algorithm. Based on this, we can use the curve fitting method to make sub-pixel subdivision of the edge position of the image, and carry out curve fitting of the edge signal. Finally, use the least square method to compare the second order curve which is obtained by fitting with the threshold level, and then use it to get the formula. We can use the formula to work out the accurate position of the edge point, thereby achieve the sub-pixel edge positioning precision. The experimental results and analysis show that, compared with the threshold level comparison method, the straight line fitting method has more advantages, such as high repeated precision, good stability and so on. It can restrain the influence of random noise effectively, so it can detect the edge position of one-dimensional image effectively.
Keywords
curve fitting; edge detection; 1D image; curve fitting; edge automatic detecting algorithm; edge positioning precision; edge signal; image edge gray degree; image measurement; least square method; linear CCD scan image; second order curve; straight line fitting method; sub-pixel edge detection; Charge coupled devices; Charge-coupled image sensors; Curve fitting; Image edge detection; Least squares methods; Object detection; Optical sensors; Pixel; Signal detection; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Computing Science, 2009. ICIC '09. Second International Conference on
Conference_Location
Manchester
Print_ISBN
978-0-7695-3634-7
Type
conf
DOI
10.1109/ICIC.2009.205
Filename
5169089
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