Discriminative non-negative representation based classifier for image recognition. (September 2021)

• Record Type: Journal Article
• Authors: Hu, Kai-Jun; Yin, He-Feng; Sun, Jun
• Is Part Of: Journal of algorithms & computational technology. Volume 15(2021)
• Publication Date: 2021-09
• Subjects: Image recognition -- non-negative representation -- representation based classification -- decorrelation regularizer; Computer algorithms -- Periodicals; Numerical calculations -- Periodicals; Computer algorithms; Numerical calculations; Periodicals; 518.1
• DOI: 10.1177/17483026211044922
• Languages: English
• ISSNs: 1748-3018

Abstract

During the past decade, representation based classification method has received considerable attention in the community of pattern recognition. The recently proposed non-negative representation based classifier achieved superb recognition results in diverse pattern classification tasks. Unfortunately, discriminative information of training data is not fully exploited in non-negative representation based classifier, which undermines its classification performance in practical applications. To address this problem, we introduce a decorrelation regularizer into the formulation of non-negative representation based classifier and propose a discriminative non-negative representation based classifier for pattern classification. The decorrelation regularizer is able to reduce the correlation of representation results of different classes, thus promoting the competition among them. Experimental results on benchmark datasets validate the efficacy of the proposed discriminative non-negative representation based classifier, and it can outperform some state-of-the-art deep learning based methods. The source code of our proposed discriminative non-negative representation based classifier is accessible athttps://github.com/yinhefeng/DNRC .