CLC number: TP751
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2013-09-16
Cited: 1
Clicked: 8355
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.
@article{title="Curve length estimation based on cubic spline interpolation in gray-scale images",
author="Zhen-xin Wang, Ji-hong Ouyang",
journal="Journal of Zhejiang University Science C",
volume="14",
number="10",
pages="777-784",
year="2013",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1300056"
}
%0 Journal Article
%T Curve length estimation based on cubic spline interpolation in gray-scale images
%A Zhen-xin Wang
%A Ji-hong Ouyang
%J Journal of Zhejiang University SCIENCE C
%V 14
%N 10
%P 777-784
%@ 1869-1951
%D 2013
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1300056
TY - JOUR
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
VL - 14
IS - 10
SP - 777
EP - 784
%@ 1869-1951
Y1 - 2013
PB - Zhejiang University Press & Springer
ER -
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.
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