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Relaxed support vector based dictionary learning for image classification

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Abstract

Discriminative dictionary learning (DDL) has attracted significant attention in the field of image classification. To enhance the classification performance, most existing discriminative dictionary learning methods introduce supervision information on the dictionary to project raw training samples into a coefficient subspace. However, the strict constraint on coefficient features may not conducive to the separation of the training samples from different classes for dictionary learning. In this paper, we propose Relaxed Support Vector based Dictionary Learning (RSVDL) for image recognition, which can efficiently learn coefficient features with powerful discrimination and representation capabilities. By constructing a relaxed coefficient subspace that is closely associated with label information, the discriminative of the learned dictionary is also improved. Experimental results on several benchmark datasets show that the proposed RSVDL method is very effective for various image classification tasks. Moreover, the experiments on more challenging datasets further reveal the state-of-art performance of our method by using with the CNN features.

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Data Availability

The data used during this study are public datasets, which can be obtained directly in the references, also we can provide them if the requirement.

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Acknowledgements

This paper is supported by the Project of Science and Technology of Henan (No. 232102210049), the Science and Technology Foundation of Guizhou Province (Nos. QKHJC[2020]1Y253, QKHJC-ZK[2022]YB024), the Higher Education Teaching Reform Research and Practice Project of Henan (No. 2021SJGLX271), the third batch of First class undergraduate courses in Henan Province “Information Theory and Coding” (Department of Higher Education[2022], No. 324), the first batch of Undergraduate college curriculum ideological and political model course in Henan Province “Information Theory and Coding” (Department of Higher Education[2020], No. 531), and the Research Start-up Foundation of Dr. Song Jianqiang (No. BSJ2022026).

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  1. College of Electronic Information and Electric Engineering, Anyang Institute of Technology, Anyang, 455000, China

    Jianqiang Song, Chaochen Xie, Chao Lu, Jianzhou Zhao & Suling Gao

  2. School of Mathematics and Statistics, Guizhou University of Finance and Economics, Guiyang, 550025, China

    Zuozhi Liu

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Song, J., Liu, Z., Xie, C. et al. Relaxed support vector based dictionary learning for image classification. Multimed Tools Appl 83, 12731–12755 (2024). https://doi.org/10.1007/s11042-023-15907-8

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