International Journal of Science, Technology and Society

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An Approach for Eliminating Restrictions on the Synthesis of Quality Classifiers of Fruits and Vegetables

Received: 22 August 2014    Accepted: 30 August 2014    Published: 20 September 2014
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Abstract

Synthesis of classifiers of agricultural products by quality is related with two main tasks –selection symptoms for object description in new space and choice of method for pattern recognition for objects separation in quality classes. A special feature of agricultural products as objects of classification is the different size of their primary descriptions. This feature imposes restrictions on the choice of symptoms and a method for pattern recognition in the synthesis of the classifier. The work proposes an algorithm for unification of the primary descriptions of classified products using interpolation methods. Different methods of interpolation are compared and the one which provides the simplest algorithm is recommended for use. The algorithm is applied to a virtual extension of experimentally derived primary descriptions of potato tubers. The new extended descriptions are applied to the synthesis of the symptoms and classifier. Simulation testing of the classifier, synthesized with the new and original descriptions of the products was conducted in Matlab. The applicability of the proposed algorithm to unify the descriptions of classified agricultural products is proved. The proposed approach removes the restrictions on the choice of method for the synthesis of symptoms and method for pattern recognition and reduces the number of training set of objects.

DOI 10.11648/j.ijsts.20140205.13
Published in International Journal of Science, Technology and Society (Volume 2, Issue 5, September 2014)
Page(s) 109-114
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Qualification of Agricultural Products, Interpolation, Classifier, Pattern Recognition

References
[1] A. Georgiev, L. Kostadinova, Automated systems for qualification and sorting agricultural products, Journal ”Food Industry” №6, Sofia, Bul, 1985.
[2] A. Georgiev, L. Kostadinova, R. Gabrova, On–line Sorting Apples in Modern Technologies for Providing Quality of Fruit and Vegetable in Chains, Acta Horticulturae, N 712, Proc. Of the IV Intern. Conf. on Managing Quality in Chains, vol. 2, p. 911–914, MQUIC2006, Bangkok, Thailand, 2006.
[3] A. Georgiev, L. Kostadinova, R. Gabrova, N. Shopov, Increasing the Rate of Operation of Automatic Quality Classifiers for Agricultural products – Software and Hardware Decisions, Acta Horticulturae, N858,p. 431-438, March, 2010
[4] I. Witten, F. Eibe, Data Mining Practical Machine Learning Tools and Techniques, Morgan Kaufmann Publishers Inc. San Francisco, CA, USA, 2005.
[5] L. Kostadinova, A. Georgiev, R. Gabrova, N. Shopov, Improving the Automatic Classifiers in Systems for on-line “Tracing” the Quality of Agricultural Products, Proceedings Vol. 1 of UNITECH’07. Gabrovo, p.465-469, Bul, 2007.
[6] L. Kostadinova, A. Georgiev, N. Shopov, Informational Aspects of the Processes in Objectively Determining the Quality of Food, , Proceedings Vol. 1 of UNITECH’10. Gabrovo, p.I-548-I-553, Bul, 2010.
[7] N. Shopov, A. Georgiev, L. Kostadinova, R. Gabrova, Generating symptoms’ spaces by orthogonal basis functions during automatic qualification of products, Proceedings Vol.1 of UNITECH’07, Gabrovo, p. 420-425, Bul, 2007.
[8] R. Burden, D. Faires D, Numerical Analysis 9th Brooks/Cole, USA, 2011.
[9] S. Chapra, R. Canale, Numerical methods for Engineers 6th ed., McGraw–Hill Higher Companies, USA, 2010.
[10] S. Donevska, B. Donevski, Fast Fourier Transform, Sofia, Bul, 1999.
Author Information
  • Dept. Computer systems and technologies, University of Food Technologies, Plovdiv, Bulgaria

  • Dept. Computer systems and technologies, University of Food Technologies, Plovdiv, Bulgaria

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  • APA Style

    Radoslava Nikolova Gabrova, Lena Filipova Kostadinova-Georgieva. (2014). An Approach for Eliminating Restrictions on the Synthesis of Quality Classifiers of Fruits and Vegetables. International Journal of Science, Technology and Society, 2(5), 109-114. https://doi.org/10.11648/j.ijsts.20140205.13

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    ACS Style

    Radoslava Nikolova Gabrova; Lena Filipova Kostadinova-Georgieva. An Approach for Eliminating Restrictions on the Synthesis of Quality Classifiers of Fruits and Vegetables. Int. J. Sci. Technol. Soc. 2014, 2(5), 109-114. doi: 10.11648/j.ijsts.20140205.13

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    AMA Style

    Radoslava Nikolova Gabrova, Lena Filipova Kostadinova-Georgieva. An Approach for Eliminating Restrictions on the Synthesis of Quality Classifiers of Fruits and Vegetables. Int J Sci Technol Soc. 2014;2(5):109-114. doi: 10.11648/j.ijsts.20140205.13

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  • @article{10.11648/j.ijsts.20140205.13,
      author = {Radoslava Nikolova Gabrova and Lena Filipova Kostadinova-Georgieva},
      title = {An Approach for Eliminating Restrictions on the Synthesis of Quality Classifiers of Fruits and Vegetables},
      journal = {International Journal of Science, Technology and Society},
      volume = {2},
      number = {5},
      pages = {109-114},
      doi = {10.11648/j.ijsts.20140205.13},
      url = {https://doi.org/10.11648/j.ijsts.20140205.13},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijsts.20140205.13},
      abstract = {Synthesis of classifiers of agricultural products by quality is related with two main tasks –selection symptoms for object description in new space and choice of method for pattern recognition for objects separation in quality classes. A special feature of agricultural products as objects of classification is the different size of their primary descriptions. This feature imposes restrictions on the choice of symptoms and a method for pattern recognition in the synthesis of the classifier. The work proposes an algorithm for unification of the primary descriptions of classified products using interpolation methods. Different methods of interpolation are compared and the one which provides the simplest algorithm is recommended for use. The algorithm is applied to a virtual extension of experimentally derived primary descriptions of potato tubers. The new extended descriptions are applied to the synthesis of the symptoms and classifier. Simulation testing of the classifier, synthesized with the new and original descriptions of the products was conducted in Matlab. The applicability of the proposed algorithm to unify the descriptions of classified agricultural products is proved. The proposed approach removes the restrictions on the choice of method for the synthesis of symptoms and method for pattern recognition and reduces the number of training set of objects.},
     year = {2014}
    }
    

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  • TY  - JOUR
    T1  - An Approach for Eliminating Restrictions on the Synthesis of Quality Classifiers of Fruits and Vegetables
    AU  - Radoslava Nikolova Gabrova
    AU  - Lena Filipova Kostadinova-Georgieva
    Y1  - 2014/09/20
    PY  - 2014
    N1  - https://doi.org/10.11648/j.ijsts.20140205.13
    DO  - 10.11648/j.ijsts.20140205.13
    T2  - International Journal of Science, Technology and Society
    JF  - International Journal of Science, Technology and Society
    JO  - International Journal of Science, Technology and Society
    SP  - 109
    EP  - 114
    PB  - Science Publishing Group
    SN  - 2330-7420
    UR  - https://doi.org/10.11648/j.ijsts.20140205.13
    AB  - Synthesis of classifiers of agricultural products by quality is related with two main tasks –selection symptoms for object description in new space and choice of method for pattern recognition for objects separation in quality classes. A special feature of agricultural products as objects of classification is the different size of their primary descriptions. This feature imposes restrictions on the choice of symptoms and a method for pattern recognition in the synthesis of the classifier. The work proposes an algorithm for unification of the primary descriptions of classified products using interpolation methods. Different methods of interpolation are compared and the one which provides the simplest algorithm is recommended for use. The algorithm is applied to a virtual extension of experimentally derived primary descriptions of potato tubers. The new extended descriptions are applied to the synthesis of the symptoms and classifier. Simulation testing of the classifier, synthesized with the new and original descriptions of the products was conducted in Matlab. The applicability of the proposed algorithm to unify the descriptions of classified agricultural products is proved. The proposed approach removes the restrictions on the choice of method for the synthesis of symptoms and method for pattern recognition and reduces the number of training set of objects.
    VL  - 2
    IS  - 5
    ER  - 

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