A comparison of methods for extracting information from the co-occurrence matrix for subcellular classification

作者：

Highlights：

• Cell phenotype image classification by ensemble of descriptors.

• Compare some recently proposed methods that are based on the co-occurrence matrix.

• Investigate the correlation among the features that can be extracted from the co-occurrence matrix.

• Determine the best way to combine co-occurrence matrix based feature sets.

摘要

•Cell phenotype image classification by ensemble of descriptors.•Compare some recently proposed methods that are based on the co-occurrence matrix.•Investigate the correlation among the features that can be extracted from the co-occurrence matrix.•Determine the best way to combine co-occurrence matrix based feature sets.

论文关键词：Texture descriptors,Co-occurrence matrix,Subcellular localization,Support vector machine,Random subspace

论文评审过程：Available online 24 July 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.07.047