结合自适应图像片与图割的交互式图像分割算法研究
关键词 图像分割 非局部 图像片 图割
毕业论文设计说明书外文摘要
Title The research on combining adaptive patch and the interactive image segmentation based on graph cut
Abstract
The interactive image segmentation algorithm based on graph cut has attracted considerable attention due to its simple interaction, better segmentation results and other features. For image with simple background, user only need to provide less seeds and then the graph cut algorithm can automatically obtain a satisfactory segmentation result. However it always obtains a satisfactory result difficultly for image with noise and texture. In order to overcome above problems and further improve the accuracy of the segmentation, in this paper, patch-level information is effective introduced into the traditional graph cut model, in which the more accurate feature is utilized by comparing the similarities between two patches. The segmentation methods based on patches usually introduce the patch-level information into the boundary term of the energy function, which would dramatically increase the time complexity due to the similarity computations of all patches. To effectively utilize the patch information in graph cut model, in this paper, we first utilize the Gaussian mixture model (GMM) to construct the structural features of patches. Therefore, the patch-level information can be obtained based on the learning of GMM. Then we combine the pixel-level information and patch-level information together to further improve the segmentation accuracy for the details around boundary regions. The performance of our proposed approach demonstrates its improved robustness and effectiveness.
Keywords Image segmentation Nonlocal Image patch Graph cut
目 次
1 绪论 1
1.1 图像分割研究背景 1
1.2 交互式图像分割研究现状 2
1.3 本文主要内容及章节安排 4
2 图像分割的理论基础 5
2.1 图像分割的定义 5
2.2 图像分割方法的分类 6
2.3 分割特征及描述方法 6
2.4 本章小结 9
3 基于图割理论的图像分割 10
3.1 图理论 10
3.2 s-t网络流图与其割 11
3.3 基于图割理论的图像分割 12
3.4 基于非局部方法的模型 14
3.5 本章小结 15
4 结合像素和图像片的图像分割算法 16
4.1 高斯混合模型 16
4.2 本文算法 17
4.3 实验结果与分析 21
4.4 本章小结 25
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