Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling
International Journal of Computer Vision
Selection of the optimal prototype subset for 1-NN classification
Pattern Recognition Letters
Statistical and neural classifiers: an integrated approach to design
Statistical and neural classifiers: an integrated approach to design
Estimation of Dependences Based on Empirical Data: Springer Series in Statistics (Springer Series in Statistics)
Contour detection based on nonclassical receptive field inhibition
IEEE Transactions on Image Processing
Grayscale aerial and space image colorization using texture classification
Pattern Recognition Letters - Special issue: Pattern recognition in remote sensing (PRRS 2004)
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Common groves consist of single trees, forests and glades. Their decipherment involves three main components: trees and forests detection with recognition of their textures, contour segmentation and reconstruction of forest stand parameters. They can both be simple parameters such as tree height, crown closure etc. or complex parameters such as species components. It is shown that using textural prototype matching can solve all three tasks. The experiments show relatively high reliability of the proposed technique: 65-70% for special components reconstruction and 77-82% for direct forest stand parameters.