• Spectroscopy and Spectral Analysis
  • Vol. 42, Issue 7, 2218 (2022)
Jie-kai YANG1、1;, Zhi-qiang GUO1、1;, Yuan HUANG2、2; 3; *;, Hong-sheng GAO1、1;, Ke JIN1、1;, Xiang-shuai WU2、2;, and Jie YANG1、*
Author Affiliations
  • 11. College of Information Engineering, Hubei Key Laboratory of Broadband Wireless Communication and Sensor Network, Wuhan University of Technology, Wuhan 430070, China
  • 22. College of Horticulture and Forestry Sciences, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
  • show less
    DOI: 10.3964/j.issn.1000-0593(2022)07-2218-07 Cite this Article
    Jie-kai YANG, Zhi-qiang GUO, Yuan HUANG, Hong-sheng GAO, Ke JIN, Xiang-shuai WU, Jie YANG. Early Classification and Detection of Melon Graft Healing State Based on Hyperspectral Imaging[J]. Spectroscopy and Spectral Analysis, 2022, 42(7): 2218 Copy Citation Text show less
    Hyperspectral image collection
    Fig. 1. Hyperspectral image collection
    Overall research plan
    Fig. 2. Overall research plan
    Segmentation diagram(a): Segmentation of region of interest and background region; (b): Spectra of region of interest and background region; (c): Mask
    Fig. 3. Segmentation diagram
    (a): Segmentation of region of interest and background region; (b): Spectra of region of interest and background region; (c): Mask
    CARS-SPA algorithm(a): Feature band extracted by CARS algorithm;(b): Feature band extracted by CARS-SPA algorithm
    Fig. 4. CARS-SPA algorithm
    (a): Feature band extracted by CARS algorithm;(b): Feature band extracted by CARS-SPA algorithm
    The choice of grafting difference information(a): Average spectra of grafted survival and non-viable seedlings on the 7th day; (b): Average absorption spectra of grafted survival and non-viable seedlings on the 7th day; (c): Location of the extracted feature wavelengths using DIS-CARS-SPA algorithm
    Fig. 5. The choice of grafting difference information
    (a): Average spectra of grafted survival and non-viable seedlings on the 7th day; (b): Average absorption spectra of grafted survival and non-viable seedlings on the 7th day; (c): Location of the extracted feature wavelengths using DIS-CARS-SPA algorithm
    天数P/%
    SGFDSDMSCSNVSG-SDSNV-SDSNV-SG-SD
    199.1199.1199.3399.3399.3399.3399.3399.0599.33
    298.8298.8299.7699.7699.2999.7699.56100.00100.00
    396.7397.0198.6399.2398.0999.1899.2599.1899.87
    498.1198.1197.6499.0598.0298.8598.8699.0299.58
    597.3497.5899.0399.1598.5599.0399.0899.03100.00
    696.5496.0498.3698.8598.1598.3697.9899.3899.69
    797.8597.6299.6499.8199.0499.2599.8699.76100.00
    Table 1. Two classification results of grafted survival seedlings and non-viable seedlings on the same day based on SVM constructed by different pretreatments
    类型P/%
    ABCDA-BA-CB-CA-D
    嫁接成活苗90.1797.6899.15-99.3399.6599.23-
    嫁接非成活苗97.03--99.76---99.95
    Table 2. Two classification results of survival/non-viable seedlings grafted on different days using SVM constructed based on SNV-SG-SD pretreatment
    输入类型预处理特征提取分类模型特征波段数P/%
    1~7 d甜瓜嫁接苗SNV-SG-SDCARS-SPASVM(RBF)3296.26
    1~7 d甜瓜嫁接苗SNV-SG-SDDIS-CARS-SPASVM(RBF)2696.85
    1~7 d甜瓜嫁接苗SNV-SG-SD-SVM(RBF)15093.48
    Table 3. Fourteen classification results of grafted survival/non-viable seedlings by SVM based on feature extraction after SNV-SG-SD preprocessing
    输入类型预处理特征提取分类模型SVM参数P/%
    1~7 d甜瓜嫁接苗SNV-SG-SDDIS-CARS-SPAGS-SVM(RBF)c=1 000, g=1 00096.85
    1~7 d甜瓜嫁接苗SNV-SG-SDDIS-CARS-SPAPSO-SVM(RBF)c=1 000, g=1087.89
    1~7 d甜瓜嫁接苗SNV-SG-SDDIS-CARS-SPAQPSO-SVM(RBF)c=1 000, g=10092.62
    1~7 d甜瓜嫁接苗SNV-SG-SDDIS-CARS-SPAGA-SVM(RBF)c=100, g=1075.32
    1~7 d甜瓜嫁接苗SNV-SG-SDDIS-CARS-SPAQGA-SVM(RBF)c=100, g=10085.27
    Table 4. Parameter selection of SVM model based on different optimization algorithms
    输入类型预处理特征提取分类模型核函数P/%
    1~7 d甜瓜嫁接苗SNV-SG-SDDIS-CARS-SPAGS-SVMRBF96.85
    1~7 d甜瓜嫁接苗SNV-SG-SDDIS-CARS-SPAGS-SVMLINEAR61.33
    1~7 d甜瓜嫁接苗SNV-SG-SDDIS-CARS-SPAGS-SVMPOLY76.95
    1~7 d甜瓜嫁接苗SNV-SG-SDDIS-CARS-SPAGS-SVMSIGMOID50.36
    Table 5. Parameter selection of SVM model based on different kernel functions
    Jie-kai YANG, Zhi-qiang GUO, Yuan HUANG, Hong-sheng GAO, Ke JIN, Xiang-shuai WU, Jie YANG. Early Classification and Detection of Melon Graft Healing State Based on Hyperspectral Imaging[J]. Spectroscopy and Spectral Analysis, 2022, 42(7): 2218
    Download Citation