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Research on Technology of Twin Image Recognition Based on the Multi-feature Fusion

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Social Computing (ICYCSEE 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 624))

Abstract

In order to improve the accuracy and stability of fruit and vegetable image recognition by single feature, this project proposed multi-feature fusion algorithms and SVM classification algorithms. This project not only introduces the Reproducing Kernel Hilbert space to improve the multi-feature compatibility and improve multi-feature fusion algorithm, but also introduces TPS transformation model in SVM classifier to improve the classification accuracy, real-time and robustness of integration feature. By using multi-feature fusion algorithms and SVM classification algorithms, experimental results show that we can recognize the common fruit and vegetable images efficiently and accurately.

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Acknowledgments

This paper has been supported by the National Natural Science Foundation of China (Grant No. 61371040).

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, 150080, China

    Yanqing Wang & Yipu Wang

  2. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China

    Chaoxia Shi

  3. Henan Electric Power Transmission and Transformation Engineering Company, Zhengzhou, 450051, China

    Hui Shi

Authors
  1. Yanqing Wang
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  2. Yipu Wang
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  3. Chaoxia Shi
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  4. Hui Shi
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Corresponding author

Correspondence to Yanqing Wang .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology , Harbin, China

    Wanxiang Che

  2. Harbin Engineering University , Harbin, China

    Qilong Han

  3. Harbin Institute of Technology , Harbin, China

    Hongzhi Wang

  4. Northeast Forestry University , Harbin, China

    Weipeng Jing

  5. National University of Defense Technology , Changsha, China

    Shaoliang Peng

  6. Harbin Engineering University , Harbin, China

    Junyu Lin

  7. Harbin Univ. of Science and Technology , Harbin, China

    Guanglu Sun

  8. Harbin Univ. of Science and Technology , Harbin, China

    Xianhua Song

  9. Harbin Engineering University , Harbin, China

    Hongtao Song

  10. Harbin Sea of Clouds & Computer Tech. , Harbin, China

    Zeguang Lu

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© 2016 Springer Science+Business Media Singapore

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Cite this paper

Wang, Y., Wang, Y., Shi, C., Shi, H. (2016). Research on Technology of Twin Image Recognition Based on the Multi-feature Fusion. In: Che, W., et al. Social Computing. ICYCSEE 2016. Communications in Computer and Information Science, vol 624. Springer, Singapore. https://doi.org/10.1007/978-981-10-2098-8_21

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  • DOI: https://doi.org/10.1007/978-981-10-2098-8_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2097-1

  • Online ISBN: 978-981-10-2098-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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