Discriminate of Moldy Chestnut Based on Near Infrared Spectroscopy and Feature Extraction by Fourier Transform - Computer and Computing Technologies in Agriculture IV - Part I Access content directly
Conference Papers Year : 2011

Discriminate of Moldy Chestnut Based on Near Infrared Spectroscopy and Feature Extraction by Fourier Transform

Zhu Zhou
  • Function : Author
  • PersonId : 1012431
Xiaoyu Li
  • Function : Author
  • PersonId : 1012432
Peiwu Li
  • Function : Author
  • PersonId : 1012433
Yun Gao
  • Function : Author
  • PersonId : 1012434
Jie Liu
  • Function : Author
  • PersonId : 1012435
Wei Wang
  • Function : Author
  • PersonId : 1012436

Abstract

As near infrared spectra has the characters of multi-variables and strong correlations, to solve the problem, Fourier transform (FT) was used to extract feature variables of shelled chestnuts spectra. FT coefficients and the status of 178 chestnuts were selected as inputs and outputs of the back-propagation neural network (BPNN) classifier to build a recognition model. For comparison, principal component analysis (PCA) was utilized to compress the variables, which then was introduced as input of the neural network model. The results demonstrate that FT is a powerful feature extraction method and is better than PCA as a feature extraction method when employed together with BPNN. When the preprocessing method of standard normal variate transformation(SNV) was carried out and the first 15-point FT coefficients were used as the input, an optimal network structure of 15-6-1 was obtained, where discriminating rates of qualified chestnut, surface moldy chestnut and internal moldy chestnut in prediction set are 100%, 100% and 92.31%, respectively.
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hal-01559610 , version 1 (10-07-2017)

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Zhu Zhou, Xiaoyu Li, Peiwu Li, Yun Gao, Jie Liu, et al.. Discriminate of Moldy Chestnut Based on Near Infrared Spectroscopy and Feature Extraction by Fourier Transform. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. pp.600-607, ⟨10.1007/978-3-642-18333-1_73⟩. ⟨hal-01559610⟩
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