基于先验色彩协方差约束的彩色图像分割  

Color Image Segmentation Based on Prior Color Covariance Constraint

作　　者：彭浩[1] 周新志[1] 雷印杰[1] 

机构地区：[1]四川大学电子信息学院,成都610065

出　　处：《计算机工程》2017年第4期251-256,共6页Computer Engineering

基　　金：国家"973"计划项目"基于负载特性的微波源实时智能控制理论与关键技术"(2013CB328903);国家自然科学基金"基于四元数的非约束4D人脸识别方法研究"(61403265)

摘　　要：利用矢量活动轮廓C-V模型分割背景亮度高、目标区域亮度低且目标色彩不连续的彩色图像时,目标区域分割效果不理想。针对该问题,构建一种先验色彩协方差与C-V模型相结合的彩色图像分割模型。设计局部Sigmoid函数对曲线演化时的内外部区域能量进行局部处理,提升分割速度。给出先归级后精细的二次分割框架和背景区域处理机制以保证彩色图像的精细分割,解决因亮度而造成的分割歧义问题。实验结果表明,该模型能够快速准确地分割出目标区域,并且分割区域的内部均匀性较好。When using vector active contours C-V model for image segmentation in the background with high brightness, target region with low brightness and image with discontinuous target color, the segmentation effect of target region is not ideal. Aiming at this problem,this paper constructs a color image segmentation model combined with prior color covariance and C-V model. It designs local Sigmoid function to process internal and external regional energies of curve evolution to accelerate the process of segmentation. For avoiding the segmentation ambiguity by brightness, it proposes secondary segmentation framework and background regional process system to ensure the fine segmentation of color image. Experimental result shows that the proposed model can extract the target region quickly and accurately. The segmented regions are with higher degree of internal homogeneity.

关 键 词：C-V模型 先验色彩协方差 SIGMOID函数 背景区域处理 二次分割 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]