非交互式GrabCut图像分割方法

Hanning Wang, Jiang Wang, Chuangzhan Zeng, Chen Wang
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引用次数: 0

摘要

基于图论原理的GrabCut图像分割算法在计算机视觉领域得到了广泛的应用。但缺点是需要人机交互来完成感兴趣区域的选择,以解决前景图像的分割任务。因此,它不能满足全智能图像处理的要求。为了消除人机交互,实现智能区域选择,本文提出了一种ROI智能区域生成和微调方法,对GrabCut方法进行改进,从而实现智能图像分割。实验结果表明,该方法兼容单目标和多目标前景图像分割方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-interactive GrabCut image segmentation method
The GrabCut image segmentation algorithm based on the principle of graph theory has been extensively used in the field of computer vision. However, the shortcoming is that it requires human-computer interaction to complete the ROI region selection to solve the segmentation task of the foreground image. Therefore, it cannot meet the requirements of fully intelligent image processing. In order to eliminate human-computer interaction and realize smart region selection, this paper proposes a ROI smart region generating and fine-tuning method to improve the GrabCut method, so as to realize intelligent image segmentation. The experimental results show that our method is compatible with both single-target and multi-target foreground image segmentation solutions.
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