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Image Feature Extract and Performance Analysis Based on Slant Transform

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Computational Intelligence and Intelligent Systems (ISICA 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 575))

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Abstract

In order to improve the efficient and simple the steps of generation an image hashing, a security and robustness image hashing algorithm based on Slant transform (ST) is proposed in this paper. By employing coefficients of Slant transform, a robust hashing sequence is obtained by preprocessing, feature extracting and post processing. The security of proposed algorithm is totally depended on the user-key which are saved as secret keys. For illustration, several benchmark images are utilized to show the feasibility of the image hashing algorithm. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as JPEG compression, mid-filtering, and rotation. Therefore, the scheme proposed in this paper is suitable for image authentication, content-based image retrieval and digital watermarking, etc.

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Acknowledgments

The work presented in this paper was supported by Guangdong Provincial Science and Technology Program (No. 2014A020208139); Distinguished Young Talents in Higher Education of Guangdong (No. 2013LYM-0057). Delong Cui is corresponding author.

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Authors and Affiliations

  1. College of Computer and Electronic Information, Guangdong University of Petrochemical Technology, Maoming, China

    Jinglong Zuo, Delong Cui & Qirui Li

  2. Information Centre, Dongguan Power Supply Bureau, Guangdong Power Grid Co, Dongguan, China

    Hui Yu

Authors
  1. Jinglong Zuo
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  2. Delong Cui
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  3. Hui Yu
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  4. Qirui Li
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Corresponding author

Correspondence to Delong Cui .

Editor information

Editors and Affiliations

  1. College of Mathematics and Informatics, The South China Agricultural University, Guangzhou, China

    Kangshun Li

  2. School of Computer Science, Guangzhou University, Guangzhou, China

    Jin Li

  3. School of Computer Science and Engineeri, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

  4. Dept. of Informatics, University of Salerno, Fisciano, Italy

    Aniello Castiglione

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© 2016 Springer Science+Business Media Singapore

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Zuo, J., Cui, D., Yu, H., Li, Q. (2016). Image Feature Extract and Performance Analysis Based on Slant Transform. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_52

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  • DOI: https://doi.org/10.1007/978-981-10-0356-1_52

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0355-4

  • Online ISBN: 978-981-10-0356-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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