IDENTIFICATION OF NANGUO PEAR MATURITY BASED ON INFORMATION FUSION
Abstract
Maturity is not only an important factor affecting the internal quality of the Nanguo pear, but also an important theoretical basis for grading online fruit. Based on the hyperspectral imaging technology, in this paper, back-propagation neural network and support vector machine models are established to identify Nanguo pear maturity by information fusion of spectral features and image features. The results show that the identification results of the support vector machine based on information fusion of spectral features and image features are the best, and the recognition rate is above 95%. Among them, the recognition rates of immature and mature samples reach 100%.
About the Authors
Dongmin Yu
College of Information and Electrical Engineering, Shenyang Agricultural University; Shenyang Polytechnic College
China
Shenyang 110866; Shenyang 110045
China
Shenyang 110866; Shenyang 110045
Tongyu Xu
College of Information and Electrical Engineering, Shenyang Agricultural University
China
China
Shenyang 110866
Kai Song
Shenyang Ligong University
China
Shenyang 110159
China
Shenyang 110159
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Review
For citations:
Yu D., Xu T., Song K. IDENTIFICATION OF NANGUO PEAR MATURITY BASED ON INFORMATION FUSION. Zhurnal Prikladnoii Spektroskopii. 2020;87(2):346(1)-346(8).
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