In this paper

we propose an adaptive spectral clustering algorithm based on the Nyström method with multi-level structures in LUV color space.First

we introduce the LUV color space

which can effectively avoid the influence of barely noticeable differences on the segmentation results

achieving better result in texture and edge regions.Second

we combine the spectral clustering algorithm based on multi-level structure and the Nyström method.Our approach can reduce the operation time and solve the problem of memory overflow.Finally

in -means

through the analysis of the eigengap to adaptive select the value of

this approach can automatically determine the number of clusters.The proposed method is applied to image segmentation

respectively

in LUV color space and RGB color space.The experimental results show that in LUV color space we can obtain even better results.The data computation and operation time as well as the segmentation result of the proposed algorithm are superior

compared to the spectral clustering algorithm based on the Nyström method (SC-N).