Journal of Terahertz Science and Electronic Information Technology , Volume. 18, Issue 4, 687(2020)

Rapid classification of northeast rice varieties based on hyperspectral imagery

SI Gangzheng, YUE Xin, LYU Zhong, YANG Heng, WANG Shengnan, LI Fengjiao, SONG Shaozhong, WEN Changli, and TAN Yong*
Author Affiliations
  • [in Chinese]
  • show less

    Based on the nondestructive identification requirements of rice varieties, the spectral image features of three rice samples are analyzed by hyperspectral technique, and the detection, classification and identification of three kinds of rice using Liquid Crystal Tunable Filter(LCTF) spectral camera are realized. The VIS/NIR(Visible/Near-Infrared) spectral images of rice samples are collected by hyperspectral camera, and the hyperspectral image is processed and analyzed by Matlab and ENVI software. The relative reflectance curves of each sample are obtained. By using image threshold segmentation technology, the spectral images of each band are obtained. Combining the images and data, the spectral differences of different varieties of rice are analyzed. It is found that the rice had a distinct characteristic peak in the 480-550 nm band. The spectral differences between different varieties are obvious, and the ratios of the brightness of the binary images for different varieties of rice are different as well. The results show that the relative reflectivity and binary image of spectral images have good prospects in the application of rapid classification and identification of rice varieties.

    Tools

    Get Citation

    Copy Citation Text

    SI Gangzheng, YUE Xin, LYU Zhong, YANG Heng, WANG Shengnan, LI Fengjiao, SONG Shaozhong, WEN Changli, TAN Yong. Rapid classification of northeast rice varieties based on hyperspectral imagery[J]. Journal of Terahertz Science and Electronic Information Technology , 2020, 18(4): 687

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Aug. 12, 2019

    Accepted: --

    Published Online: Dec. 25, 2020

    The Author Email: Yong TAN (laser95111@126.com)

    DOI:10.11805/tkyda2019297

    Topics