Combining Region and Edge Cues for Image Segmentation in a Probabilistic Gaussian Mixture Framework

Omer Rotem, H. Greenspan, J. Goldberger
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引用次数: 30

Abstract

In this paper we propose a new segmentation algorithm which combines patch-based information with edge cues under a probabilistic framework. We use a mixture of multiple Gaussians for building the statistical model with color and spatial features, and we incorporate edge information based on texture, color and brightness differences into the EM algorithm. We evaluate our results qualitatively and quantitatively on a large data-set of natural images and compare our results to other state-of-the-art methods.
结合区域和边缘线索的概率高斯混合框架图像分割
本文提出了一种在概率框架下将基于补丁的信息与边缘线索相结合的分割算法。我们使用混合的多个高斯函数来构建具有颜色和空间特征的统计模型,并将基于纹理、颜色和亮度差异的边缘信息纳入EM算法。我们在大量自然图像数据集上定性和定量地评估我们的结果,并将我们的结果与其他最先进的方法进行比较。
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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