iipp publishingJournal of Applied Engineering Science

Article

Robust classification of texture landforest inventory based on model of minimally sufficient features
ISSN: 1451-4117
E-ISSN: 1821-3197
DOI:10.5937/jaes15-14060 
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions.

Volume 15 article 436 pages: 236 - 241

Yury Ipatov*
Volga State University of Technology, Yoshkar-Ola, Russia

Alexandr Krevetsky
Volga State University of Technology, Yoshkar-Ola, Russia

Yury Andrianov
Volga State University of Technology, Yoshkar-Ola, Russia

Boris Sokolov
Saint Petersburg Institute of Informatics and Automation, Russian Academy of Sciences
(SPIIRAS), Saint Petersburg, Russia

Method for automated classification of ground forest inventory images based on the proposed mathematical model developed. The general model is represented by the statistical characteristics of images and fractal dimension of texture. Experimental means were determined minimally sufficient characteristics to solve the problem of robust classification. Neural network based on unsupervised self-organizing maps used as a classifier. Figures obtained discounts of the proposed approach on real digital images.

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