A New Image Segmentation Model

Abstract:

To build a new image segmentation model based on level set theory : Add edge detection operator to edgeless active contour model to detect local information; introduce adaptive coefficient of area item to let the model autonomously adjust and evolve curve position according to image information; adopt weighted average gray value to replace traditional absolute mean value to reduce error and improve segmentation result. Experimental result comparison shows that the new model can detect global information and local information at the same time, adaptively adjust curve evolution direction, and has a fast segmentation speed. Compared to edgeless active contour model, the new model is a more effective image segmentation method as it has greater advantages in image segmentation accuracy and computational complexity.

• Periodical: Applied Mechanics and Materials (Volumes 519-520)
• Pages: 541-547
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.519-520.541
• Online since: February 2014
• Authors: Chao Liu*, Jing Liu, Lu Lu Zhang
• Keywords: Adaptive, Edge Detection, Image Segmentation, Level Set

References

[1] Osher S., Sethian J. A., Fronts propagating with curvature dependent speed: Algorithms based on the Hamilton-Jacobi formulation. Journal of Computational Physics, 1988, 79, 12-49.

DOI: 10.1016/0021-9991(88)90002-2

[2] Adalsteinsson D, Sethian J. A fast level set method for propagating interfaces. J Compphys. May 1995, 118(2): 269-277.

DOI: 10.1006/jcph.1995.1098

[3] Malladi R, SethianJ. A, VemuriB.C. Shape modeling with front propagation: alevel set approach. IEEE Trans Patt Anal Mach Intel l. February 1995, 17(2): 158-175.

DOI: 10.1109/34.368173

[4] Tony F. Chan, Luminita A. Vese. Active Contours Without Edges. IEEE Transactions on Image Processing , VOL. 10. NO. 2, February (2001).

DOI: 10.1109/83.902291

[5] Mumford D, Shah J. Optimal approximations by Piecewise smooth functions and associated variational problems. Commun pure APPI Math. 1989, 42(5): 577-685.

DOI: 10.1002/cpa.3160420503

[6] Shih F. Y, Cheng s. Adaptive mathematical morphology for edge linking . Information Sciences. 2004, 167(l-4): 9-21.

DOI: 10.1016/j.ins.2003.07.020

[7] Xue-Min Yin, Jian-Ping Guo, Chong-Fa Zhong, Yu-Hua Yao, Zhe Zhang, Yi Wei. Multi-region level set image segmentation based on image cartoon-texture decomposition model. ISBB 2011, pp.92-95, (2011).

DOI: 10.1109/isbb.2011.6107653

[8] Jing Liu, Xiao-mei Zhu, Chao Liu, Parameter-adaptive image segmentation based on variational level set method. ICIC Express Letters, v 7, n 9, pp.2581-2585, (2013).