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Research on Crop Growth Period Estimation Based on Fusion Features

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Advances in Artificial Intelligence and Security (ICAIS 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1423))

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Abstract

Automatic recognition of crop growth period is one of the core parts of precision agriculture support technology. In order to identify different growth periods in real time and obtain crop growth information, a crop growth period estimation method based on fusion features is proposed. First, the crop images are preprocessed to filter out the noise. Then the HOG features, SILTP features and color features are fused. Finally, XQDA is used to measure the similarity to classify and identify the growing period of crops.

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Author information

Authors and Affiliations

  1. Ecological and Agricultural Meteorological Center, Shijiazhuang Meteorological Bureau, Shijiazhuang, 050000, China

    Qi Gao

  2. School of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050000, China

    Xing Sun

Authors
  1. Qi Gao
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  2. Xing Sun
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Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Xiaorui Zhang

  3. Jinan University, Guangzhou, China

    Zhihua Xia

  4. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Gao, Q., Sun, X. (2021). Research on Crop Growth Period Estimation Based on Fusion Features. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Advances in Artificial Intelligence and Security. ICAIS 2021. Communications in Computer and Information Science, vol 1423. Springer, Cham. https://doi.org/10.1007/978-3-030-78618-2_37

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  • DOI: https://doi.org/10.1007/978-3-030-78618-2_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78617-5

  • Online ISBN: 978-3-030-78618-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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