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首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >Image segmentation using modified SLIC and Nystr?m based spectral clustering
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Image segmentation using modified SLIC and Nystr?m based spectral clustering

机译:使用改进的SLIC和基于Nystr?m的光谱聚类进行图像分割

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摘要

Image segmentation is a fundamental and challenging problem in the field of computer vision. In this paper, an efficient two-stage image segmentation method is proposed which takes advantage of modified SLIC segmentation and Nystr?m based spectral clustering. With the modified SLIC approach utilized in the first stage, Nystr?m based spectral clustering method is used to cluster the segmented regions instead of the pixels in the image to bring the final result. Therefore, the memory requirement and the computational complexity are significantly reduced. To verify the proposed algorithm, it is applied to images of different characters and compared with six other famous image segmentation approaches. Experiment results show the effectiveness and the robustness of the proposed method.
机译:图像分割是计算机视觉领域中的一个基本且具有挑战性的问题。本文提出了一种有效的两阶段图像分割方法,该方法利用了改进的SLIC分割和基于Nystr?m的谱聚类技术。通过在第一阶段中使用改进的SLIC方法,基于Nystr?m的光谱聚类方法被用于聚类分割的区域,而不是图像中的像素以产生最终结果。因此,显着降低了内存需求和计算复杂度。为了验证该算法的有效性,将其应用于不同字符的图像,并与其他六种著名的图像分割方法进行了比较。实验结果表明了该方法的有效性和鲁棒性。

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