Title :
Plant species identification using fuzzy set theory
Author :
Nabout, A. ; Gerhards, R. ; Su, Bing ; Eldin, H. A Nour ; Kuhbauch, W.
Author_Institution :
Group of Autom. Control & Tech. Cybern., Wuppertal Univ., Germany
Abstract :
The automatic identification of plant species is a great challenge because their patterns are complex and uncertain. In this paper, the fuzzy set theory was applied to identify weed species. A membership function was established. The experiment has shown, that the average rate of correct identification has improved from 67% to greater than 82%
Keywords :
biology computing; fuzzy set theory; pattern recognition; automatic identification; correct identification rate; fuzzy set theory; membership function; plant species identification; weed species; Automatic control; Chemicals; Cybernetics; Decision making; Fuzzy set theory; Fuzzy sets; Image processing; Optimization methods; Pattern recognition; Protection;
Conference_Titel :
Image Analysis and Interpretation, 1994., Proceedings of the IEEE Southwest Symposium on
Conference_Location :
Dallas, TX
Print_ISBN :
0-8186-6250-6
DOI :
10.1109/IAI.1994.336686
