基于改进的GrabCut算法的图像分割  

Image Segmentation Based on the Improved GrabCut Algorithm

作　　者：丁一[1] 梅娟[1] DING Yi;MEI Juan(Wuxi City College of Vocational Technology,Wuxi,Jiangsu Province,214000 China)

机构地区：[1]无锡城市职业技术学院,江苏无锡214000

出　　处：《大众科学》2024年第9期1-3,共3页China Public Science

基　　金：江苏省高等教育教改研究课题——产教融合引领下《数据库原理及应用》教学内容提升与教学模式重构(项目编号:2023JSJG553)。

摘　　要：图像分割技术是图像处理中的一个重要步骤,它帮助计算机理解图像并找出其中的不同部分.GrabCut是该领域中的一种算法,它使用图论模型和马尔科夫随机场来帮助计算机更好地分割彩色图像.这种算法的特点是分割结果很好,只需要很少的人工干预.介绍了一个改进的GrabCut算法,通过实验表明:该算法在处理复杂彩色图像时,分割的准确性更高、更稳定.与其他算法相比,该算法在分割结果的精确度上有所提高,有效解决了处理多目标彩色图像时容易出现大面积分割错误的问题.Image segmentation is an important step in image processing,which helps computers understand images and identify their different parts.GrabCut is one of the algorithms in this field,which uses the graph theory model and the Markov random field to assist computers in better segmenting color images,and its feature is that it has good segmentation results and only requires minimal human intervention.This paper introduces an improved GrabCut algorithm.Through experiments,it is shown that the algorithm has higher and stabler accuracy when segmenting complex color images,and that compared to other algorithms,it has improved the accuracy of segmentation results,which effectively addresses the issue of large-scale segmentation errors when processing multi-object color images.

关 键 词：图像分割 GrabCut算法 背景检测 模式识别 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]