基于GAC模型实现交互式图像分割的改进算法

An improved algorithm of interactive image segmentation based on GAC model

提出了一种改进的交互式图像分割算法。采用全变分去噪模型对图像进行预处理,在去除噪声的同时更好地保护了边缘;提出了一种对梯度模值进行曲率加权的边缘检测方法,采用该方法获得图像的边缘点集;将边缘点集中曲率较大的边缘点作为候选边界点推荐给用户;用户通过主观判断,在候选边界点中选择合适的"初始边界点",算法便可采用GAC模型完成对目标的分割。实验结果表明,改进算法提高了交互式图像分割的自动化程度,有效地减少了交互过程中的人工参与量。

This paper advances an improved algorithm for interactive image segmentation. Firstly, it adoptes the total variation model to pretreat the image so that the edge of the image is well protected while denoising; Second, it advances an edge detection algorithm according to the curvature-weighted gradient module to acquire aggregate of the points in boundary;Thirdly, it recommends these points of the bigger curvature as candidate ones to the user;Finally, the user chooses appropriate points according to their judgement, then the computer will achieve the object＇s segmentation on GAC model. Experiments given show that the improved algorithm significantly enhances the automatization level of interactive image segmentation, and effectively reduces workload in the interactive course.