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论文类型：会议论文

发表时间：2016-01-01

收录刊物：CPCI-S

页面范围：524-524

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

摘要：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.