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This research concentrated on an assessment of the sensitivity of five selected textural feature groups focused on changes in contrast, brightness, sharpness, and rotation of image. The analyzed texture images were real samples of asbestos roofs. During the study, MaZda software was used for determining 259 different textural features. The obtained results were analyzed to indicate insensitive parameters while transforming the sample image. There were no textural features found in the received results, which were simultaneously resistant to all of the implemented changes .

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ABSTRACT:The classification of urban fabric can be achieved using the information of individual buildings and measure their distance to all image objects in the map. The distance to a variety of building types return various areas, which can be associated with dense and less dense urban fabric. The resulting classification can be used as an alternative or as a control mechanism on normal urban fabric classification. The method can be used to extend existing manuals on urban fabric.