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Clustering Analysis Based on Segmented Images

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Machine Learning and Intelligent Communications (MLICOM 2017)

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Abstract

Image segmentation plays an important role in the field of digital production management. Image resolution is an important factor affecting the size of its segmentation and segmentation efficiency, and the physical characteristics of the image capturing device is another important factor. With high-resolution segmentation algorithm in image segmentation, we often find that the edge contour image segmentation is difficult to accurately determine, more complex image arithmetic operation efficiency is not high and images taken with a different device in response to segmentation algorithms are very different. In this paper, the plant leaf image collected from different cameras was used as the object of study, and the feature quantity was extracted. The appropriate segmentation boundary was determined by cluster analysis. The leaf image was pretreated with the resolution adjustment, and the leaf image was in the appropriate segmentation feature range. After the clustering domain processing of the feature range in this paper, it solves the problem that the real edge of the leaf area information is too difficult to distinguish, and effectively solves the problem of complex image algorithm and ordinary pc machine in the process of complex image processing Efficiency issues. The appropriate segmentation feature range of the devices is established for different devices, which effectively solves the different response of different devices to the segmentation algorithm.

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Acknowledgments

This work was supported by the Beijing ‘The agricultural technology promotion information project in Hebei Province’ program and was undertaken by China Agricultural University.

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Authors and Affiliations

  1. College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, China

    Hongxu Zheng, Jianlun Wang & Can He

Authors
  1. Hongxu Zheng
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  2. Jianlun Wang
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  3. Can He
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Corresponding author

Correspondence to Jianlun Wang .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, Heilongjiang, China

    Xuemai Gu

  2. Harbin Institute of Technology, Weihai, Heilongjiang, China

    Gongliang Liu

  3. Shandong University, Weihai, Heilongjiang, China

    Bo Li

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zheng, H., Wang, J., He, C. (2018). Clustering Analysis Based on Segmented Images. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 226. Springer, Cham. https://doi.org/10.1007/978-3-319-73564-1_7

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  • DOI: https://doi.org/10.1007/978-3-319-73564-1_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73563-4

  • Online ISBN: 978-3-319-73564-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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