Spectroscopy and Spectral Analysis, Volume. 41, Issue 2, 599(2021)
Wood Species Classification With Microscopic Hyper-Spectral Imaging Based on I-BGLAM Texture and Spectral Fusion
Figures & Tables(9)
Fig. 1. Two-dimensional grayscale images of eight sample woods
(a): Red oak; (b): Merbau; (c): Talisai; (d): African padauk; (e): Basralocus; (f): Teak; (g): Silky oak; (h): Medang
Fig. 2. Image preprocessing
(a): Feature band selection; (b): Image fusion
Fig. 3. Pixel value compression results
(a): The original image; (b): Compressed image
Table 1. Details of the sample wood
View tableView in ArticleTable 1. Details of the sample wood
Number Chinese Latin 1 美国红橡 Quercus rubra 2 印尼菠萝格 Intsia bijuga 3 非洲卡斯拉 Terminalia catappa 4 红花梨 Terocarpus angolensis 5 南美柚木 Dicorynia guianensis 6 水煮柚 Tectona grandis L.F. 7 桦木 Grevillea robusta 8 香樟木 Cinnamomum camphora
Table 2. Classification accuracy using different features
View tableView in ArticleTable 2. Classification accuracy using different features
Method Texture/% Spectrum/% Texture+Spectrum/% 1 87.5 87.5 100 2 88.54 92.71 100 3 85.42 81.25 98.96 4 86.4583 89.58 98.96 5 81.25 84.38 100
Table 3. The highest classification accuracy rate of this article and other methods
View tableView in ArticleTable 3. The highest classification accuracy rate of this article and other methods
Method Accuracy/% 本文方法 100 GLCM 76.04 SPPE 64.58 文献[ 19 ]SPPD+I-BGLAM 91.67 Fuzzy+SPPD+I-BGLAM 87.5 文献[ 18 ]GA
GA+KDA68.75
48.96
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Peng ZHAO, Jin-cheng HAN, Cheng-kun WANG. Wood Species Classification With Microscopic Hyper-Spectral Imaging Based on I-BGLAM Texture and Spectral Fusion[J]. Spectroscopy and Spectral Analysis, 2021, 41(2): 599
Paper Information
Category: Research Articles
Received: Feb. 14, 2020
Accepted: May. 5, 2020
Published Online: Apr. 8, 2021
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