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Large-scale image colorization based on divide-and-conquer support vector machines

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An Erratum to this article was published on 18 March 2016

Abstract

This study presents a system that can automatically colorize grayscale images in large quantities. To enable big data training, divide-and-conquer support vector machines (SVMs) also proposed as classifiers are frequently used in this study. The system is composed of two components—image classification and local-descriptor classification. The former firstly analyzes an input by using a classifier, so that the system can determine which class should serve as the knowledge base. After the class is decided, the latter stage subsequently uses this knowledge base as the reference to colorize the input. Experimental results showed that the accuracy of classification in image classification could reach 90.50 %. Moreover, in the local-descriptor classification, the majority of pixels were successfully assigned correct colors. During the efficiency test, the proposed divide-and-conquer SVM enhanced computational speed while maintaining the accuracy. Such findings demonstrate the effectiveness of the proposed method and the feasibility of our idea.

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Acknowledgments

This work was supported in part by the Ministry of Science and Technology, the Republic of China under Grant No. 103-2917-I-564-058. Part of this research is sponsored by the Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, under the open project No. 2015-4. Furthermore, the Department of Electrical Engineering, Princeton University, supported this research during 2014/04-2015/05. No financial fund is given by Sungkyul University, South Korea. Dr. S. Rho does not participate in any creation and development of the proposed methods.

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Authors and Affiliations

  1. Department of Electrical Engineering, Princeton University, Princeton, USA

    Bo-Wei Chen, Xinyu He & Sun-Yuan Kung

  2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Wen Ji

  3. Department of Multimedia, Sungkyul University, Anyang, South Korea

    Seungmin Rho

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  1. Bo-Wei Chen
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  2. Xinyu He
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  3. Wen Ji
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  4. Seungmin Rho
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  5. Sun-Yuan Kung
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Correspondence to Bo-Wei Chen.

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Chen, BW., He, X., Ji, W. et al. Large-scale image colorization based on divide-and-conquer support vector machines. J Supercomput 72, 2942–2961 (2016). https://doi.org/10.1007/s11227-015-1414-z

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  • DOI: https://doi.org/10.1007/s11227-015-1414-z

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