作　　者： ; ; ; ;

机构地区： 浙江工业大学之江学院信息工程系

出　　处： 《浙江大学学报（工学版）》 2005年第6期830-834,共5页

摘　　要： 针对提花织物图像在噪声环境下分割精确度偏低的问题,提出了一种基于MumfordShah模型的数值求解算法.基于Gamma收敛和有界变分函数理论,将模型的极小化过程作为一个自由不连续问题来实现对含噪提花织物图像的分割.定义了分片仿射空间上的自适应三角剖分的离散公式,利用离散公式的Gamma收敛序列对模型进行数值逼近.采用自适应调整算法和有限元网格技术对提花图案轮廓结构实施表征,由共轭梯度方法得到离散公式的最小值.实验结果表明,该算法对噪声有很好的稳健性,且可以有效提高图像分割整体性能. For solving the problem of low accuracy in segmentation of jacquard images under noisy environment, a numerical implementation algorithm was proposed by using the Mumford-Shah model. Based on Gamma-convergence and bounded variation functions theories, the minimization of the model was seen as a free discontinuity problem for the segmentation of noisy jacquard images. A discrete formulation of the model was defined on piecewise affine spaces of adaptive triangulation, and the model was approximated in the sense of Gamma-convergence by a sequence of the discrete formulations. An adaptive adjustment algorithm for the triangulation and the finite element mesh technique were enforced to characterize the essential contour structure of a jacquard pattern. The conjugate gradient method was utilized to find the absolute minimum of the discrete formulation. Experimental results show that the proposed algorithm is robust against noise, and can improve the integrity of the segmentation performance.

关 键 词： 模型 共轭梯度方法 图像分割 提花织物图像

领　　域： [自动化与计算机技术] [自动化与计算机技术]