Polynomial pulp fiber modeling

This paper proposes an automatic measurement algorithm for calculating statistics of pulp fiber lengths and curvature. The fibers are extracted from digital images, and a parametric model is fit to the extracted objects. The modeling approach improves the robustness of the detection and enables connecting broken fiber parts into full length curves. The developed algorithm is compared to an alternative method, and concluded to yield similar results while providing additional features, such as curvature estimates, of the detected fibers.

[1]  John C. Russ,et al.  The Image Processing Handbook , 2016, Microscopy and Microanalysis.

[2]  Katja Schladitz,et al.  Fiber Orientation Estimation from 3D Image Data: Practical Algorithms, Visualization, and Interpretation , 2007, 7th International Conference on Hybrid Intelligent Systems (HIS 2007).

[3]  Huapeng Wang,et al.  Fiber property characterization by image processing , 2007 .

[4]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[5]  Stina Svensson,et al.  Using distance transform based algorithms for extracting measures of the fiber network in volume images of paper , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[6]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[7]  Olga Veksler,et al.  Fast Approximate Energy Minimization via Graph Cuts , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Jianmei Bian,et al.  Pulp Fibre Recognition Based on Curvelet Transform and Skeleton Tracing Algorithm , 2007, 2007 2nd IEEE Conference on Industrial Electronics and Applications.

[9]  Anders Brun,et al.  Segmentation of Wood Fibres in 3D CT Images Using Graph Cuts , 2009, ICIAP.

[10]  Fernand S. Cohen,et al.  Part I: Modeling Image Curves Using Invariant 3-D Object Curve Models-A Path to 3-D Recognition and Shape Estimation from Image Contours , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Zhengwei Yang,et al.  Invariant matching and identification of curves using B-splines curve representation , 1995, IEEE Trans. Image Process..