MINIMIZATION OF THE NUMBER OF INFORMING SIGNS WHEN CONSTRUCTING THE CLASSIFIER OF VEGETABLE OBJECTS
DOI:
https://doi.org/10.15588/1607-3274-2013-2-6Keywords:
recognition, spectral brightness coefficients, signs, classifierAbstract
In the article a possibility is considered as to decrease information features at discrimination of vegetable objects. The multiple discriminant Fisher analysis with step-by-step inclusion of variables was used as an algorithm of discrimination. The information features were selected on the basis of the subjectively individual approach. The features were selected from frequency areas in which there existed the greatest difference by a reflection coefficient value between spectral reflection coefficients for each kind of plants. The special-purpose literature on these themes was also taken into account. For the analysis of the discrimination efficiency by the classifier of plants (for a different amount of features) a probability of plant proper discrimination was used. A minimum admissible level of the correct detection probability for each kind was set as 90 %. For investigation there were used the real reflection coefficients of plants – maize, bristlegrass and ambrosia that were measured in field conditions.References
Rachkulic V. I., Sitnikova M. V. Otrazhatelnie svoystva rastitelynogo pokrova. Leningrad, Gidrometeoizdat, 1981, 287 p.
Medvedev А. V. Neparametricheskie sistemy adaptacii. Novosibirsk, Nauka, 1983, 174 p.
Piza D. М., Morshchavka S. V. Vybor naborov priznakov dlya raspoznavanie rastitelnih obektov. Sistemnyi analiz, upravlinnya i informatsiyni tehnologii: Visnyk Kharkivskogo derzhavnogo politehnichnogo universitetu. Zbirka naukovyh prats, Vypusk 97, Kharkiv, HDPU, 2000, pp. 69–74.
Daridi F., Kharma N., Salik J. Parameterless genetic algorithms: review and innovation, IEEE Canadian Review. Summer, 2004, No. 47, pp. 19–23.
Sergienko R. B. Issledovanie effektivnosti koevolyutsionnogo geneticheskogo algoritma uslovnoi optimizatsii, Vestnik Sibirskogo gosudarstvennogo aerokosmicheskogo universiteta imeni akademika M.F. Reshetneva, 2009, No. 3 (24), pp. 31–36.
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