Discriminative structured dictionary learning for image classification

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• 作者：Ping Wang 猿莿/a> ; Junhua Lan 兰俊舿/a> ; Yuwei Zang 臧玉勿/a>…
• 关键词：sparse representation ; dictionary learning ; sparse coding ; image classification
• 刊名：Transactions of Tianjin University
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：22
• 期：2
• 页码：158-163
• 全文大小：452 KB
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• 作者单位：Ping Wang 王 萍 (1)
  Junhua Lan 兰俊花 (1)
  Yuwei Zang 臧玉卫 (2)
  Zhanjie Song 宋占杰 (1)
  
  1. School of Sciences, Tianjin University, Tianjin, 300354, China
  2. Tianjin Tendbeyond Science and Technology Development Co., Ltd, Tianjin, 300072, China
  
• 刊物类别：Engineering
• 刊物主题：Chinese Library of Science
  
• 出版者：Tianjin University
• ISSN：1995-8196

文摘

In this paper, a discriminative structured dictionary learning algorithm is presented. To enhance the dictionary’s discriminative power, the reconstruction error, classification error and inhomogeneous representation error are integrated into the objective function. The proposed approach learns a single structured dictionary and a linear classifier jointly. The learned dictionary encourages the samples from the same class to have similar sparse codes, and the samples from different classes to have dissimilar sparse codes. The solution to the objective function is achieved by employing a feature-sign search algorithm and Lagrange dual method. Experimental results on three public databases demonstrate that the proposed approach outperforms several recently proposed dictionary learning techniques for classification.