Soft Image Segmentation Based on the Mixture of Gaussians and the Phase-Transition Theory

• 作者: Celia A. Z. Barcelos Fuhua Chen Yunmei Chen
• 来源期刊: 应用数学(英文)
• 学科: 工学
• 关键词: Image SEGMENTATION VARIATIONAL Model GAUSSIAN MIXTURE
• 年，卷（期）: 2014,（18）
• 页码范围: 2888-2898
• 页数: 11页
• 分类号: TP39

摘要

In this paper, we propose a new soft multi-phase segmentation model where it is assumed that the pixel intensities are distributed as a Gaussian mixture. The model is formulated as a minimization problem through the use of the maximum likelihood estimator and phase-transition theory. The mixture coefficients, which are estimated using a spatially varying mean and variance procedure, are used for image segmentation. The experimental results indicate the effectiveness of the method.