Computer Science ›› 2015, Vol. 42 ›› Issue (8): 40-43.

Previous Articles     Next Articles

Variational Level Set Method for Image Segmentation Based on Improved Signed Pressure Force Function

CAO Jun-feng, WU Xiao-jun and CHEN Su-gen   

  • Online:2018-11-14 Published:2018-11-14

Abstract: In order to handle the problem of inaccurate moving of contour which results in the wrong segmentation of the image with weak boundary and intensity inhomogeneity,a variational level set method for image segmentation based on improved signed pressure force function combined with the statistical information of image was proposed in this paper.Firstly,a new model of active contours is constructed by using a new pressure sign function to replace the edge function.Secondly,the algorithm maintains the merits of geodesic active contour(GAC) model and chan-vese(C-V) model and makes the level set function stop evolution in the boundary of the target image.Finally,simulation experiments were implemented on images with poor boundaries and intensity inhomogeneity.Experimental results show the proposed model has high computational efficiency and accuracy.Furthermore,it is robust to noise.

Key words: Active contour model,Level set,Signed pressure force,Statistical information

[1] Kass M,Witkin A,Terzopoulos D.Snakes:active contour mo-dels[J].International Journal Computer Vision,1987,1(4):321-331
[2] Caselles V,Kimmel R,Sapiro G.Geodesic Active Contours[J].International Journal of Computer Vision,1997,22(1):61-79
[3] Chan T F,Vese L A.Active Contours without Edges[J].IEEE Trans on Image Processing,2001,10(2):266-277
[4] Yuan Y,He C J.Variational level set methods for image seg-mentation based on both L2 and Sobolev gradients[J].Nonlinear Analysis:Real World Applications,2012,13:969-966
[5] Liu L H,Zeng L,Shen K,et al.Exploiting local intensity information in Chan-Vese model for noisy image segmentation[J].Signal Processing,2013,93:2709-2721
[6] Wang L,He L,Mishra A,et al.Active contours driven by local Gaussian distribution fitting energy[J].Signal Processing,2009,89:2435-2447
[7] Li D Y,Li W F,Liao Q M.Active contours driven by local and global probability distributions[J].Journal of Visual Communication and Image Representation,2013,4:533-533
[8] Osher S,Sethian J.Fronts propagating with curvature-dependent speed:Algorithms based on Hamilton-Jacobi formulations[J].Journal Computer,Physics,1988,9(1):12-49
[9] Li C M,Kao C Y,Gore J.C,et al.Implicit active contours driven by local binary fitting energy[C]∥Proc of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Washington DC,USA,2007,1:1-7
[10] Wang X F,Huang D S,Xu H.An Efficient Local Chan-VeseModel for Image Segmentation[J].Pattern Recognition,2010,43(3):603-618
[11] Vese L A,Chan T F.A multiphase level set framework for image segmentation using the Mumford and Shah model[J].International Journal of Computer Vision,2002,0:271-293
[12] Wang L,Li C M,Sun Q S,et al.Active contours driven by local and global intensity fitting energy with application to brain MR image segmentation[J].Computerized Medical Imaging and Graphics,2009,3:520-531
[13] Zhang K H,Zhang L,Song H H,et al.Active Contours with Selective Local or Global Segmentation:A New Formulation and Level Set Method[J].Image and Vision Computing,2010,28(4):668-676

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[2] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[3] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[4] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[5] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[6] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[7] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[8] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[9] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .
[10] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99, 116 .