Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (9): 176-179.

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Regional adaptive active contour model for image segmentation

XING Hui1, PENG Yali1, LIU Shigang1, FAN Hong1, SUN Jiancheng2   

  1. 1.School of Computer Science, Shaanxi Normal University, Xi’an 710062, China
    2.School of Computer Science and Technology, Xidian University, Xi’an 710071, China
  • Online:2015-05-01 Published:2015-05-15

一种区域自适应主动轮廓模型的图像分割方法

邢  辉1,彭亚丽1,刘侍刚1,范  虹1,孙建成2   

  1. 1.陕西师范大学 计算机科学学院,西安 710062
    2.西安电子科技大学 计算机学院,西安 710071

Abstract: In order to effectively segment intensity inhomogeneous image, this paper presents a regional adaptive active contour model for image segmentation. In the model, an energy function including a local energy term and a global energy term is defined. At the beginning of evolution, the force from the global energy term which is larger than the one from the local energy term is overwhelming, which has the advantages of fast convergence speed. On the contrary, in the late of evolution, the force from the local energy is overwhelming, which has the advantages of positioning precision. Experimental results show that the model can fast and effectively segment the intensity inhomogeneous images.

Key words: active contour model, level set, image segmentation

摘要: 为了有效地分割灰度不均匀图像,提出了一种区域自适应主动轮廓模型,在该模型中,定义了一个包含全局能量项和局部能量项的能量泛函。在算法的初期,全局能量项占主导地位,它具有收敛速度快、对初始轮廓不敏感的优点。在算法的后期,局部能量项占主导地位,它具有定位精度高的优点。理论分析和实验结果表明,该模型具有收敛速度快、分割精度高、对初始轮廓不敏感等优点。

关键词: 主动轮廓模型, 水平集, 图像分割