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基于划分函数的图像拟合能量驱动的活动轮廓 被引量:2

Active contours driven by image fitting energy based on division function
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摘要 为了分割灰度不均和边界模糊图像,提出了基于全局划分与局部划分的图像拟合(Division-based image fitting,DIF)活动轮廓模型。分别建立了基于划分的局部拟合和全局拟合约束项,利用权重参数将二者线性组合得到DIF模型,对活动轮廓特征的提取有一定的应用意义。DIF模型中的全局拟合约束项用于捕捉图像中目标的整体轮廓,局部拟合约束项用于捕捉图像灰度的局部变化,可较好地处理图像中灰度不均和边界模糊区域的目标边界,权重系数用于调整局部与全局能量的比重。实验结果表明,DIF模型能较好地分割灰度不均和边界模糊的图像,另外该分割方法的JS(Javascript)系数较高。 The Division-based image fitting(DIF)active contour model is proposed,to segment images with intensity inhomogeneous and blurred boundaries.The local fitting and global fitting constraint terms based on division are established respectively.The DIF model is obtained by linearly combining the two using the weight parameter,which has certain application significance for the extraction of active contour features.The global fitting constraint term in the DIF model is used to capture the overall contour of the target in the image,the local fitting constraint term is used to capture the local changes of the image grayscale,which can better deal with the uneven grayscale in the image and the target boundary in the boundary blurred region,and the weighting coefficients are used to adjust the weight of local and global energy.The experimental results show that the DIF model can segment the images with uneven grayscale and blurred boundaries better,and in addition the segmentation method has a high JS(Javascript)coefficient.
作者 熊点华 唐利明 严俊潇 胡冀万 任彦军 XIONG Dianhua;TANG Liming;YAN Junxiao;HU Jiwan;REN Yanjun(College of Mathematics,ABa Teachers University,Wenchuan 623002,China;College of Mathematics and Statistics,Hubei Minzu University,Enshi 445000,China;College of Information Engineering,Tarim University,Alaer 843300,China)
出处 《黑龙江大学自然科学学报》 CAS 2022年第4期481-489,共9页 Journal of Natural Science of Heilongjiang University
基金 国家自然科学基金资助项目(62061016,61561019)。
关键词 划分函数 图像拟合 活动轮廓 JS系数 division function image fitting active contour JS coefficient
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  • 1徐国香.UST-4条干仪的测试及应用[J].毛纺科技,2007,35(9):54-57. 被引量:3
  • 2Du X J, Cho D W, Bui T D. Image segmentation and inpaintingusing hierarchical level set and texture mapping[J]. SignalProcessing, 2011, 91(4): 852-863. 被引量:1
  • 3Estellers V, Zosso D, Lai R, et al. Efficient algorithm for levelset method preserving distance function[J]. IEEE Transactionson Image Processing, 2012, 21(12): 4722-4734. 被引量:1
  • 4Xie X M, Wang C M, Zhang A J, et al. A robust level set methodbased on local statistical information for noisy imagesegmentation[J]. Optik-International Journal for Light andElectron Optics, 2014, 125(9): 2199-2204. 被引量:1
  • 5Caselles V, Kimmel R, Sapiro G. Geodesic active contours[J].International Journal of Computer Vision, 1997, 22(1): 61-79. 被引量:1
  • 6He N, Lu K, Bao H. An improved geometric active contourmodel for concrete CT Image segmentation based on edge flow[J]. Chinese Journal of Electronics, 2010, 19(4): 687-690. 被引量:1
  • 7Liu S G, Peng Y. A local region-based Chan-Vese model forimage segmentation[J]. Pattern Recognition, 2012, 45(7): 2769-2779. 被引量:1
  • 8Zhang K H, Song H H, Zhang L. Active contours driven by localimage fitting energy[J]. Pattern Recognition, 2010, 43(4):1199-1206. 被引量:1
  • 9Yu C Y, Zhang W S, Yu Y Y, et al. A novel active contour modelfor image segmentation using distance regularization term[J].Computers & Mathematics with Applications, 2013, 65(11):1746-1759. 被引量:1
  • 10Chan T F, Vese L A. Active contours without edges[J]. IEEETransactions on Image Processing, 2001, 10(2): 266-277. 被引量:1

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