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Front. Inform. Technol. Electron. Eng.  2013, Vol. 14 Issue (10): 777-784    DOI: 10.1631/jzus.C1300056
    
Curve length estimation based on cubic spline interpolation in gray-scale images
Zhen-xin Wang, Ji-hong Ouyang
College of Computer Science and Technology, Jilin University, Changchun 130012, China; MOE Key Laboratory of Symbolic Computation and Knowledge Engineering, Jilin University, Changchun 130012, China
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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.

Key wordsArc length estimation      Cubic spline interpolation      Gray-scale image      Local algorithm     
Received: 28 February 2013      Published: 08 October 2013
CLC:  TP751  
Cite this article:

Zhen-xin Wang, Ji-hong Ouyang. Curve length estimation based on cubic spline interpolation in gray-scale images. Front. Inform. Technol. Electron. Eng., 2013, 14(10): 777-784.

URL:

http://www.zjujournals.com/xueshu/fitee/10.1631/jzus.C1300056     OR     http://www.zjujournals.com/xueshu/fitee/Y2013/V14/I10/777


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

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.

关键词: Arc length estimation,  Cubic spline interpolation,  Gray-scale image,  Local algorithm 
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