Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (11): 193-197.DOI: 10.3778/j.issn.1002-8331.1709-0326

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Algorithm for image segmentation of Chan-Vese model using radial basis point interpolation

LI Shuling   

  1. School of Mathematical Sciences, Chongqing Normal University, Chongqing 401331, China
  • Online:2018-06-01 Published:2018-06-14



  1. 重庆师范大学 数学科学学院,重庆 401331

Abstract: The level set based Chan-Vese model is a representative geometric active contour model that has been successfully applied to a variety of image segmentation problems. To enhance the computational efficiency and the segmentation accuracy of the model, an efficient numerical algorithm is developed to solve the Chan-Vese model by using the radial basis point interpolation. By approximating the level set function with the radial basis point interpolation, the Chan-Vese model is discretized into an initial?value?problem?for?ordinary?differential?equations, which can be solved by the forward Euler’s method. This algorithm is free of grids and insensitive to initial contours, gets rid of the time-consuming re-initialization, and has a stop criterion with no presetting iteration number. Experimental results show that the algorithm segments images accurately even with no initial contour and possesses high segmentation speed.

Key words: image segmentation, Chan-Vese model, radial basis function, radial basis point interpolation, level set

摘要: 基于水平集方法的Chan-Vese模型是一种典型的几何活动轮廓模型,已成功应用于众多领域中的图像分割问题。为了提高该模型的演化速度和分割效果,提出了一种基于径向基点插值求解Chan-Vese模型的高效数值算法。通过用径向基点插值法逼近水平集函数,Chan-Vese模型被离散为常微分方程组初值问题并可用向前Euler法求解。该算法不需要网格单元,对水平集初始轮廓不敏感,不涉及复杂费时的重新初始化过程,并且有明确的演化终止条件,无需事先设置演化次数。实验表明该算法在没有初始轮廓时也能正确分割图像,具有很快的演化速度。

关键词: 图像分割, Chan-Vese模型, 径向基函数, 径向基点插值法, 水平集