基于非负弹性网稀疏编码算法的图像分类方法

doi:10.3969/j.issn.1000-3428.2017.07.040

计算机工程

基于非负弹性网稀疏编码算法的图像分类方法

张勇^1a,1b,2,张阳阳 ^1a,程洪^1b,张艳霞^1a

(1.电子科技大学 a.数学科学学院; b.自动化工程学院,成都 611731; 2.大数据研究中心,成都 611731)

收稿日期:2016-06-28 出版日期:2017-07-15 发布日期:2017-07-15
作者简介:张勇(1974—),男,副教授、博士,主研方向为图像处理、机器学习;张阳阳,硕士研究生;程洪,教授;张艳霞,硕士。
基金资助:
国家自然科学基金(11271001);中央高校基本科研业务费专项资金(ZYGX2014Z012)。

Image Classification Method Based on Non-negative Elastic Net Sparse Coding Algorithm

ZHANG Yong^1a,1b,2,ZHANG Yangyang ^1a,CHENG Hong^1b,ZHANG Yanxia ^1a

(1a.School of Mathematical Science; 1b.School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China; 2.Big Data Research Center,Chengdu 611731,China)

Received:2016-06-28 Online:2017-07-15 Published:2017-07-15

摘要/Abstract

摘要：

为提高图像分类的准确率,提出一种非负弹性网稀疏编码算法。利用非负稀疏编码算法和弹性网模型,在稀疏编码优化模型的目标函数中引入l2范数正则项,增加编码系数的非负约束,并将该算法与空间金字塔模型相结合应用于图像分类。实验结果表明,与传统的稀疏编码算法相比,该算法不仅能提高编码的判别性与有效性,而且可使相似的特征描述符编码后仍然相似,增强编码的稳定性,具有较高的分类准确度。

关键词: 图像分类, 稀疏编码, 空间金字塔匹配, 弹性网, 字典学习, 支持向量机

Abstract:

In order to improve the image classification accuracy,this paper proposes a Non-negative Elastic Net Sparse Coding(NENSC)algorithm.This algorithm combines the advantages of non-negative sparse coding and elastic net algorithm.It introduces an l2norm regularization term to the objective function of Sparse Coding(SC) optimization model and non-negative constraints to coding coefficients are applied.The proposed algorithm combined with Spatial Pyramid Matching(SPM) model is applied to image classification.Experimental results show that,compared with the traditional sparse coding algorithm,the proposed algorithm not only increases the prediction capability and effectiveness of the coding,but also makes the similar feature descriptors similar after coding and improves the stability of the coding,it has higher classification accuracy.

Key words: image classification, Sparse Coding(SC), Spatial Pyramid Matching(SPM), elastic net, dictionary learning, Support Vector Machine(SVM)

中图分类号:

TP391

张勇,张阳阳,程洪,张艳霞. 基于非负弹性网稀疏编码算法的图像分类方法[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2017.07.040.

ZHANG Yong,ZHANG Yangyang,CHENG Hong,ZHANG Yanxia. Image Classification Method Based on Non-negative Elastic Net Sparse Coding Algorithm[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2017.07.040.

http://www.ecice06.com/CN/Y2017/V43/I7/239

参考文献

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