|
|
|
|
|
|
| Classifications of Oilseed Rape and Weeds Based on Hyperspectral Imaging |
| PAN Ran-ran, LUO Yi-fan, WANG Chang, ZHANG Chu, HE Yong, FENG Lei* |
| College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China |
|
|
|
|
Abstract A classification method of oilseed rape and weeds based on hyperspectral information was put forward. Standard normal variate transformation (SNV), de-trending, multiplicative scatter correction (MSC), moving average (MA), savitzky-golay smoothing(SG), baseline and normalize were applied to data preprocess. Principal component analysis loadings (PCA loadings), x-loading weights, regression coefficient (RC) and successive projection algorithm (SPA) were used to extract feature wavelengths. Partial least-squares discriminant analysis (PLS-DA), extreme learning machine (ELM) and support vector machine(SVM) were employed to establish classification models. The overall results shows that the ELM models with the selected wavelengths of PCA loadings, x-loading weights and SPA based on de-trending preprocessed spectra has obtained the best results, with 100% classification accuracy for both the calibration set and the prediction set. The index of average classification accuracy is introduced to evaluate classification models accuracy under different experimental time. The results indicates that it is feasible to use near-infrared hyperspectral imaging to identify the oilseed rape and weeds.
|
|
Received: 2016-07-10
Accepted: 2016-11-20
|
|
|
|
Corresponding Authors:
FENG Lei
E-mail: lfeng@zju.edu.cn
|
|
[1] HE Xiong-kui(何雄奎). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2004, 20(1): 13.
[2] YIN Jian-jun, SHEN Bao-guo, CHEN Shu-ren, et al(尹建军，沈宝国，陈树人，等). Transactions of the Chinese Society of Agricultural Machinery(农业机械学报), 2010, 41(6): 163.
[3] Geol P K, Prasher S O, Patel R M, et al. Transactions of the ASAE, 2002, 45(2): 443.
[4] Zhang Yun, Erik S Staab, David C Slaughter, et al. Crop Protection, 2012, 41: 96.
[5] Slaughter D C, Giles D K, Downey D. Computers and Electronics in Agriculture, 2008, 61(1): 63.
[6] CHEN Shu-ren, ZOU Hua-dong, WU Rui-mei, et al(陈树人，邹华东，吴瑞梅，等). Transactions of the Chinese Society of Agricultural Machinery(农业机械学报), 2013, 44(5): 253.
[7] ZU Qin, ZHANG Shui-fa, CAO Yang, et al(祖 琴，张水发，曹 阳，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2015, 35(2): 479.
[8] Goel P K, Prasher S O, Landry J A, et al. Transactions of the ASAE, 2003, 46(2): 539.
[9] Xie J, Pan T and Chen J M, et al. Chinese Journal of Analytical Chemistry, 2010, 38(3): 342.
[10] Lan Y, Soh Y C, Huang G B. Neurocomputing, 2009, 72(13-15): 3391.
[11] FAN Jin-song, FANG Ting-jian(范劲松，方廷健). Pattern Recognition and Artificial Intelligence(模式识别与人工智能), 2000, 13(4): 419.
[12] Chong I G, Jun C H. Chemometrics and Intelligent Laboratory Systems, 2005, 78(1-2): 103.
[13] Araujo M C U, Saldanha T C B, Galvao R K H, et al. Chemometrics and Intelligent Laboratory Systems, 2001, 57(2): 65.
[14] FENG Lei, CHEN Shuang-shuang, FENG Bin, et al(冯 雷，陈双双，冯 斌，等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报)，2012，28(1)：139. |
| [1] |
LE Ba Tuan1, 3, XIAO Dong1*, MAO Ya-chun2, SONG Liang2, HE Da-kuo1, LIU Shan-jun2. Coal Classification Based on Visible, Near-Infrared Spectroscopy and CNN-ELM Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2107-2112. |
| [2] |
CAO Xiao-feng, REN Hui-ru, LI Xing-zhi, YU Ke-qiang*, SU Bao-feng*. Discrimination of Winter Jujube’s Maturity Using Hyperspectral Technique Combined with Characteristic Wavelength and Spectral Indices[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2175-2182. |
| [3] |
YANG Ke-ming, ZHANG Wei, WANG Xiao-feng, SUN Tong-tong, CHENG Long. Differentiation and Level Monitoring of Corn Leaf Stressed by Cu and Pb Derived from Spatial Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2200-2208. |
| [4] |
HUANG Yu-ping1,3, Renfu Lu2, QI Chao1, CHEN Kun-jie1*. Tomato Maturity Classification Based on Spatially Resolved Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2183-2188. |
| [5] |
CAI Liang-hong1, 2, DING Jian-li1, 2*. Prediction for Soil Water Content Based on Variable Preferred and Extreme Learning Machine Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2209-2214. |
| [6] |
HUANG Di-yun, LI Jing-bin*, YOU Jia, KAN Za. The Classification of Delinted Cottonseeds Varieties by Fusing Image Information Based on Hyperspectral Image Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2227-2232. |
| [7] |
XIE Ya-ping1, CHEN Feng-nong1, ZHANG Jing-cheng1, ZHOU Bin2, WANG Hai-jiang3, WU Kai-hua1*. Study on Monitoring of Common Diseases of Crops Based on Hyperspectral Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2233-2240. |
| [8] |
ZHANG Jing, LIU Zhong-bao*, SONG Wen-ai, FU Li-zhen, ZHANG Yong-lai. Stellar Spectra Classification Method Based on Multi-Class Support Vector Machine[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2307-2310. |
| [9] |
GAO Pan1, ZHANG Chu3, Lü Xin2*, ZHANG Ze2, HE Yong3*. Visual Identification of Slight-Damaged Cotton Seeds Based on Near Infrared Hyperspectral Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1712-1718. |
| [10] |
CHEN Bing1, WANG Gang4, LIU Jing-de1*, MA Zhan-hong2, WANG Jing3, LI Tian-nan1, 2. Extraction of Photosynthetic Parameters of Cotton Leaves under Disease Stress by Hyperspectral Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1834-1838. |
| [11] |
TAO Chao1*, WANG Ya-jin1, ZOU Bin1, 2, TU Yu-long1, JIANG Xiao-lu1. Assessment and Analysis of Migrations of Heavy Metal Lead and Zinc in Soil with Hyperspectral Inversion Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1850-1855. |
| [12] |
XU Wei-jie1, WU Zhong-chen1, 2*, ZHU Xiang-ping2, ZHANG Jiang1, LING Zong-cheng1, NI Yu-heng1, GUO Kai-chen1. Classification and Discrimination of Martian-Related Minerals Using Spectral Fusion Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1926-1932. |
| [13] |
YAN Meng-ge1,3, DONG Xiao-zhou1,3, LI Ying2, ZHANG Ying2, BI Yun-feng1,3*. Classification of Geological Samples with Laser-Induced Breakdown Spectroscopy Based on Self-Organizing Feature Map Network and Correlation Discrimination Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1874-1879. |
| [14] |
WANG Chao, WANG Jian-ming, FENG Mei-chen, XIAO Lu-jie, SUN Hui, XIE Yong-kai, YANG Wu-de*. Hyperspectral Estimation on Growth Status of Winter Wheat by Using the Multivariate Statistical Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1520-1525. |
| [15] |
CAO Xiao-lan1, 2, CHEN Xing-ming2, ZHANG Shuai2, CUI Guo-xian1*. Ramie Variety Identification Based on the Hyperspectral Parameters and the Stepwise Discriminant Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1547-1551. |
|
|
|
|
