Indirect immunofluorescence image classification using texture descriptors

作者：

Highlights：

• A “pyramidal application” of local binary patterns coupled with a method for handling nonuniform bins is proposed.

• A preprocessing algorithm improve the results in indirect immunofluorescence image classification.

• A set of SVM is combined by weighted sum rule.

• An ensemble of approaches obtains the best performance.

摘要

•A “pyramidal application” of local binary patterns coupled with a method for handling nonuniform bins is proposed.•A preprocessing algorithm improve the results in indirect immunofluorescence image classification.•A set of SVM is combined by weighted sum rule.•An ensemble of approaches obtains the best performance.

论文关键词：Texture descriptors,Local binary patterns,Support vector machine,Ensemble,HEp-2 cells classification

论文评审过程：Available online 10 October 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.09.046