Active Contours with Thresholding Value for Image Segmentation

Gang Chen, Haiying Zhang, I-Ping Chen, Wen Yang
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引用次数: 5

Abstract

In this paper, we propose an active contour with threshold value to detect objects and at the same time get rid of unimportant parts rather than extract all information. The basic ideal of our model is to introduce a weight matrix into region-based active contours, which can enhance the weight for the main parts while filter the weak intensity, such as shadows, illumination and so on. Moreover, we can choose threshold value to set weight matrix manually for accurate image segmentation. Thus, the proposed method can extract objects of interest in practice. Coupled partial differential equations are used to implement this method with level set algorithms. Experimental results show the advantages of our method in terms of accuracy for image segmentation.
基于阈值的活动轮廓图像分割
本文提出了一种带有阈值的活动轮廓来检测目标,同时去除不重要的部分,而不是提取所有的信息。我们的模型的基本理念是在基于区域的活动轮廓中引入一个权值矩阵,该矩阵可以增强主要部分的权值,同时过滤弱强度,如阴影、光照等。此外,我们可以手动选择阈值设置权值矩阵,以实现准确的图像分割。因此,该方法可以在实际中提取出感兴趣的对象。采用耦合偏微分方程和水平集算法实现该方法。实验结果表明了该方法在图像分割精度方面的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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