基于稀疏表示全局字典学习的图像分类方法

doi:10.11772/j.issn.1001-9081.2015.02.0499

计算机应用 ›› 2015, Vol. 35 ›› Issue (2): 499-501.DOI: 10.11772/j.issn.1001-9081.2015.02.0499

基于稀疏表示全局字典学习的图像分类方法

蒲国林¹, 邱玉辉²

1. 四川文理学院计算机学院, 四川达州 635000;
2. 西南大学计算机与信息科学学院, 重庆 400715

收稿日期:2014-09-11 修回日期:2014-11-20 出版日期:2015-02-10 发布日期:2015-02-12
通讯作者: 邱玉辉
作者简介:蒲国林(1971-),男,四川宣汉人,副教授,博士,CCF会员,主要研究方向:人工智能、服务计算; 邱玉辉(1938-),男,重庆人,教授,博士生导师,主要研究方向:人工智能、大数据。
基金资助:
国家自然科学基金资助项目(61152003)。

Image classification based on global dictionary learning method with sparse representation

PU Guolin¹, QIU Yuhui²

1. School of Computer Science, Sichuan University of Arts and Science, Dazhou Sichuan 635000, China;
2. College of Computer and Information Science, Southwest University, Chongqing 400715, China

Received:2014-09-11 Revised:2014-11-20 Online:2015-02-10 Published:2015-02-12

摘要/Abstract

摘要：

针对传统的稀疏表示字典学习图像分类方法在大规模分布式环境下效率低下的问题,设计一种基于稀疏表示全局字典的图像学习方法。将传统的字典学习步骤分布到并行节点上,使用凸优化方法在节点上学习局部字典并实时更新全局字典,从而提高字典学习效率和大规模数据的分类效率。最后在MapReduce平台上进行并行化实验,结果显示该方法在不影响分类精度的情况下对大规模分布式数据的分类有明显的加速,可以更高效地运用于各种大规模图像分类任务中。

关键词: 字典学习, 图像分类, 稀疏表示, 大规模数据, MapReduce

Abstract:

To address the problem of low efficiency for traditional massive image classification, a sparse representation based global dictionary learning method was designed. The traditional dictionary learning steps were distributed to parallel nodes, local dictionaries were first learnt in local nodes and then a global dictionary was updated in real time by those local dictionaries and variables through using convex optimization method, thereby enhancing the efficiency of dictionary learning and classification of massive data. Experiments on the MapReduce platform show that the new algorithm has better performance than classical image classification methods without affecting the classification accuracy, and the new algorithm can be widely used in massive and distributed image classification tasks.

Key words: dictionary learning, image classification, sparse representation, massive data, MapReduce

中图分类号:

TP18
TP311

蒲国林, 邱玉辉. 基于稀疏表示全局字典学习的图像分类方法[J]. 计算机应用, 2015, 35(2): 499-501.

PU Guolin, QIU Yuhui. Image classification based on global dictionary learning method with sparse representation[J]. Journal of Computer Applications, 2015, 35(2): 499-501.

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基于稀疏表示全局字典学习的图像分类方法

Image classification based on global dictionary learning method with sparse representation

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