Robust classification of texture land forest inventory based on model of minimally sufficient features
Yury Ipatov, Alexandr Krevetsky, Yury Andrianov, Boris Sokolov · Istrazivanja i projektovanja za privredu · 2017
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.