An Approach for Eliminating Restrictions on the Synthesis of Quality Classifiers of Fruits and Vegetables
International Journal of Science, Technology and Society
Volume 2, Issue 5, September 2014, Pages: 109-114
Received: Aug. 22, 2014;
Accepted: Aug. 30, 2014;
Published: Sep. 20, 2014
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Radoslava Nikolova Gabrova, Dept. Computer systems and technologies, University of Food Technologies, Plovdiv, Bulgaria
Lena Filipova Kostadinova-Georgieva, Dept. Computer systems and technologies, University of Food Technologies, Plovdiv, Bulgaria
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.
Radoslava Nikolova Gabrova,
Lena Filipova Kostadinova-Georgieva,
An Approach for Eliminating Restrictions on the Synthesis of Quality Classifiers of Fruits and Vegetables, International Journal of Science, Technology and Society.
Vol. 2, No. 5,
2014, pp. 109-114.
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