Image Classification based on Sparse Representation and ROI

被引：0

作者：

Hui-hui, Zhao ^{[1
]}

Jun-ding, Sun ^{[1
]}

机构：

[1] Henan Polytech Univ, Sch Comp Sci & Technol, Jiaozuo 454000, Peoples R China

来源：

MECHATRONICS ENGINEERING, COMPUTING AND INFORMATION TECHNOLOGY | 2014年 / 556-562卷

关键词：

Sparse representation; regions of interest; image classification;

D O I：

10.4028/www.scientific.net/AMM.556-562.4906

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A new image classification method based on regions of interest (ROI) and sparse representation is introduced in the paper. Firstly, the saliency map of each image is extracted by different methods. Then, we choose sparse representation to represent and classify the saliency maps. Four different ROI extraction methods are chosen as examples to evaluate the performance of the proposed method. Experimental results show that it is more effective for image classification based on ROI.

引用

页码：4906 / 4910

页数：5

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