结合GAC与图割模型的彩色纹理图像分割方法  

Color-texture Image Segmentation Approach Designed by Integrating Geodesic Active Contour Model and Multilayer Graph Cut Model

作　　者：杨勇[1,2,3] 郑良仁[1] 郭玲[1] 叶阳东[3] 

机构地区：[1]黄河科技学院信息工程学院,郑州450063 [2]郑州工业应用技术学院,郑州450000 [3]郑州大学信息工程学院,郑州450060

出　　处：《系统仿真学报》2016年第9期2159-2168,共10页Journal of System Simulation

基　　金：国家自然科学基金(U1204610);国家青年科学基金(61502432)

摘　　要：提出了一种测地线活动轮廓模型(GAC)与多层图割模型相结合的彩色纹理图像分割方法。将Chan-Vese模型扩展到多类测地线活动轮廓模型,通过对每个类别进行高斯概率密度描述,它打破了区域内部恒定密度的假设。且在边缘约束项中引入了测地线,因此,它能够捕获具有凹性的边缘。对于多类能量函数的最小化,通过构建多层图割模型,利用最大流/最小割的方法可快速求得全局近似最优解。最终通过实验验证了提出的方法能够捕获凹型边界、且量化准确率高。An approach of color-texture image segmentation was proposed based on geodesic active contour model and multilayer graph cut model. As the clustering centers were commonly descripted with constant densities, the two phase Chan-vese model was extended to multiphase geodesic active contour model by using the Gaussian distribution to describe the changing density for each phase, and meanwhile the geodesic active contour was added into the proposed model, so that the presented approach could capture out the concave edge. For the minimization of the proposed energy function, a corresponded multilayer graph cut model was designed for resolving global approximated minimization by adopting maximum flow/minimum cut algorithm. Through the comparison experiment, the superiority of the proposed method can capture the concave boundary, which owns higher accuracy of the quantitative results.

关 键 词：彩色纹理 测地线 活动轮廓 图像分割 多层图割模型 

分 类 号：TP391.04[自动化与计算机技术—计算机应用技术]