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Image segmentation via manifold spectral clustering

机译:通过流形谱聚类进行图像分割

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摘要

In this paper, we propose a novel image segmentation method based on manifold spectral clustering. This method is based on the simple idea that image can be represented as the set of several manifolds which are also referred as super-pixels, and thus image segmentation problem are solved by manifold clustering. Based on this idea, we have designed a novel manifold spectral clustering method for image segmentation. The proposed method consists of four main steps: manifold generation, manifold representation, manifold distance, and manifold clustering. Experiments are performed on many different kinds of synthetic data and natural images to verify the effectiveness of the proposed method.
机译:本文提出了一种基于流形谱聚类的图像分割方法。该方法基于以下简单思想:可以将图像表示为多个流形的集合,这些流形也称为超像素,因此可以通过流形聚类来解决图像分割问题。基于此思想,我们设计了一种新颖的流形谱聚类方法进行图像分割。所提出的方法包括四个主要步骤:流形生成,流形表示,流形距离和流形聚类。对许多不同种类的合成数据和自然图像进行了实验,以验证所提出方法的有效性。

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