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CLC number: TP751

On-line Access: 2013-10-08

Received: 2013-02-28

Revision Accepted: 2013-05-06

Crosschecked: 2013-09-16

Cited: 1

Clicked: 3156

Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE C 2013 Vol.14 No.10 P.777-784

http://doi.org/10.1631/jzus.C1300056


Curve length estimation based on cubic spline interpolation in gray-scale images


Author(s):  Zhen-xin Wang, Ji-hong Ouyang

Affiliation(s):  College of Computer Science and Technology, Jilin University, Changchun 130012, China; more

Corresponding email(s):   wzhx_cc07@mails.jlu.edu.cn, ouyj@jlu.edu.cn

Key Words:  Arc length estimation, Cubic spline interpolation, Gray-scale image, Local algorithm


Zhen-xin Wang, Ji-hong Ouyang. Curve length estimation based on cubic spline interpolation in gray-scale images[J]. Journal of Zhejiang University Science C, 2013, 14(10): 777-784.

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T1 - Curve length estimation based on cubic spline interpolation in gray-scale images
A1 - Zhen-xin Wang
A1 - Ji-hong Ouyang
J0 - Journal of Zhejiang University Science C
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1300056


Abstract: 
This paper deals with a novel local arc length estimator for curves in gray-scale images. The method first estimates a cubic spline curve fit for the boundary points using the gray-level information of the nearby pixels, and then computes the sum of the spline segments’ lengths. In this model, the second derivatives and y coordinates at the knots are required in the computation; the spline polynomial coefficients need not be computed explicitly. We provide the algorithm pseudo code for estimation and preprocessing, both taking linear time. Implementation shows that the proposed model gains a smaller relative error than other state-of-the-art methods.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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