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Indexed by:会议论文

Date of Publication:2016-01-01

Included Journals:CPCI-S

Page Number:524-524

Key Words:Hep-2 cell image classification; complex networks; local binary pattern (LBP); fractal; texture image

Abstract:There is a growing interest in multilabel image classification. In this study, we proposed a novel texture classification approach combining the fractal theory and the LBP complex networks (FLCN). The complex networks were constructed based on the LBP features and the pixel relationships of the image. The suitable parameters and the combination of statistical properties on the complex networks were investigated to represent the texture of the image. The experimental results show that the FLCN method has good performance in the classifications of the segmented images and the biomedical images. In addition, the approach is more robust compared with other methods.