图像区域分割中的无监督图割方法  

Unsupervised graph cuts for image region segmentation

作　　者：赵婕[1,2] 谢刚[1] 

机构地区：[1]太原理工大学信息工程学院,山西太原030024 [2]太原大学计算机工程系,山西太原030032

出　　处：《系统工程与电子技术》2015年第6期1431-1436,共6页Systems Engineering and Electronics

基　　金：太原市科技项目人才专项基金(12024728)资助课题

摘　　要：提出一种基于图割算法的图像多区域分割方法,该方法采用核函数对数据项进行隐性的非线性映射,将原始数据映射到高维特征空间,实现图像的线性多类划分,扩展了分段常数模型的应用范围,提高了复杂区域的分割效果。由于图像边缘梯度变化剧烈,具有不连续性,在平滑项中加入图像的梯度约束条件,减少过分割。同时,采用无监督方法设置初始参数,避免了交互操作,更符合多区域分割的要求。实验结果表明,新方法不受图像内容的限制,无论是主观视觉判断还是客观定量分析,该方法都具有较好的分割效果。A multi-region image segmentation method based on graph cuts is proposed. is transformed into high-dimension feature space via the implicit nonlinear mapping of data tion, so that the effect of segmentation is improved, multi-class partition of the image is ac Original image data term by kernel func hieved and the appli cation of the piecewise constant model is extended. Due to the edge gradient of the image dramatically changes with discontinuity, the gradient constraint is introduced to smooth terms in order to reduce the over segmentation. Simultaneously, initial parameters are set by the unsupervised method without user interactions to meet the requirements of multi-region segmentation. Experiment results show that the proposed method is not restricted by the content of the image and has better segmentation results through both the subjective visual judge ment and the quantitative analysis.

关 键 词：区域分割 图割算法 核方法 边缘梯度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]