JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2018, Vol. 48 ›› Issue (2): 22-29.doi: 10.6040/j.issn.1672-3961.0.2017.067

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Color image selective segmentation under geometrical constraints

WANG Xueqin1,2, LI Shurong1, YU Yu1, WANG Jiayan1,2   

  1. 1.College of Information and Control Engineering, China University of Petroleum(East China), Qingdao 266580, Shandong, China;
    2. College of Electronic, Communication and Physics, Shandong University of Science and Technology, Qingdao 266590, Shandong, China
  • Received:2017-02-24 Online:2018-04-20 Published:2017-02-24

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Abstract: In order to solve the specific requirements of selectivity during the course of color image segmentation, an active contour-based color image segmentation method under geometrical constraints was proposed based on the gray image selective segmentation using one level set by Lavdie-Chen. A color image was treated as a whole for the gradient and the edge detection function. The velocity and direction of the curve evolution were determined by the edge detection function, the distance function defined about a set of points near the boundary of the interested region and the inner and outer polygon areas of the given points. Region information could help to overcome the drawbacks of edge functions relying on a single image gradient; the regularization algorithm was introduced to overcome the shortcomings of the poor segmentation effect in the depression;the Euler-Lagrange equation was quickly solved by the additive operator splitting method. Experimental results showed that the proposed color image segmentation method had the characteristics of high validity and high accuracy to selectively segment the wanted region.

Key words: color image, edge detection function, selective segmentation, additive operator splitting method, Euler-Lagrange equation

CLC Number: 

  • TP391
[1] GUO Q, WANG L, SHEN S. Multiple-channel local binary fitting model for medical image segmentation[J]. Chinese Journal of Electronics, 2015, 24(4): 802-806.
[2] CHEN B, ZOU Q H, PAN B B. A novel adaptive partial differential equation model for image segmentation[J]. Applicable Analysis, 2014, 93(11): 2440-2450.
[3] LI C, XU C, GUI C, et al. Level set evolution without re-initialization: a new variational formulation[C] // Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. San Diego, USA: IEEE, 2005: 430-436.
[4] ZHU G, ZHANG S, ZENG Q, et al. Boundary-based image segmentation using binary level set method [J]. Optical Engineering, 2007, 46(5): 1-3.
[5] LI C, XU C, GUI C, et al. Distance regularized level set evolution and its application to image segmentation[J]. IEEE Transactions on Image Processing, 2010, 19(12): 3243-3254.
[6] KASS M, WITKIN A, TERZOPOULOS D. Snakes: active contour models[J]. International Journal of Computer Vision, 1988, 1(4): 321-331.
[7] CASELLES V, KIMMEL R, SAPIRO G. Geodesic active contours[J]. International Journal of Computer Vision, 1997, 22(1): 61-79.
[8] 戚世乐,王美清. 自适应分割弱边缘的活动轮廓模型[J]. 山东大学学报(工学版), 2013, 43(6): 17-20. QI Shile, WANG Meiqing. Adaptive active contour model for weak boundary extraction[J]. Journal of Shandong University(Engineering Science), 2013, 43(6): 17-20.
[9] CHAN T F, VESE L A. Active contours without edges[J]. IEEE Transactions on Image Processing, 2001, 10(2): 266-277.
[10] MUMFORD D, SHAH J. Optimal approximations by piecewise smooth functions and associated variational problems[J]. Communications on Pure & Applied Mathematics, 1989, 42(5):577-685.
[11] GAO S, BUI T D. Image segmentation and selective smoothing by using Mumford-Shah model[J]. IEEE Transactions on Image Processing, 2005, 14(10):1537-1549.
[12] GOUT C, GUYADER C L, VESE L. Segmentation under geometrical conditions using geodesic active contours and interpolation using level set methods[J]. Numerical Algorithms, 2005, 39(1): 155-173.
[13] LIE J, LYSAKER M, TAI X C. A binary level set model and some applications to Mumford-Shah image segmentation[J]. IEEE Transactions on Image Processing, 2006, 15(5): 1171-1181.
[14] 任永峰, 周静波. 基于信息弥散机制的图像显著性区域提取算法[J]. 山东大学学报(工学版),2015, 45(6):1-6. REN Yongfeng, ZHOU Jingbo. An image saliency object detection algorithm based on information diffusion[J]. Journal of Shandong University(Engineering Science), 2015, 45(6): 1-6.
[15] 朱洪锦, 范洪辉, 叶飞跃,等. 基于区域合并与轮廓模型的图像序列人物轮廓分割[J]. 山东大学学报(工学版), 2014, 44(6): 8-14. ZHU Hongjin, FAN Honghui, YE Feiyue, et al. Human contour segmentation in image sequence based on region consolidation and contour model[J]. Journal of Shandong University(Engineering Science), 2014, 44(6): 8-14.
[16] RADA L, CHEN K. Improved selective segmentation model using one level-set[J]. Journal of Algorithms & Computational Technology, 2013, 7(4): 509-540.
[17] LE GUYADER C, GOUT C. Geodesic active contour under geometrical conditions: theory and 3D applications[J]. Numerical Algorithms, 2008, 48(1-3): 105-133.
[18] MALLADI R, SETHIAN J A, VEMURI B C. Shape modeling with front propagation: a level set approach[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995, 17(2):158-175.
[19] HAN X H, XIONG X, DUAN F. A new method for image segmentation based on BP neural network and gravitational search algorithm enhanced by cat chaotic mapping[J]. Applied Intelligence, 2015, 43(4): 855-873.
[20] WANG X F, MIN H, ZOU L, et al. An efficient level set method based on multi-scale image segmentation and hermite differential operator[J]. Original Research Article Neurocomputing, 2015, 188: 90-101.
[21] RADA L, CHEN K. A new variational model with dual level set functions for selective segmentation[J]. Communications in Computational Physics, 2012, 12(1): 261-283.
[22] CHAN T F, SANBERG B Y, VESE L A. Active contours without edges for vector-valued images[J]. Journal of Visual Communication and Image Representation, 2000, 11(2): 130-141.
[23] 樊淑炎, 丁世飞. 基于多尺度的改进Graph cut算法[J]. 山东大学学报(工学版), 2016, 46(1): 28-33. FAN Shuyan, DING Shifei. An improved multi-scale graph cut algorithm[J]. Journal of Shandong University(Engineering Science), 2016, 46(1): 28-33.
[24] BADSHAH N, CHEN K. Image selective segmentation under geometrical constraints using an active contour approach[J]. Communications in Computational Physics, 2010, 7(4): 759-778.
[25] RADA L, CHEN K. A variational model and its numerical solution for local, selective and automatic segmentation[J]. Numerical Algorithms, 2014, 66(2): 399-430.
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