In this paper we propose a simple and efficient method of image classification in UAV monitoring application. Taking into consideration the color distribution two types of texture feature are considered: statistical and fractal characteristics. In the learning phase four different and efficient features were selected: energy, correlation, mean intensity and lacunarity on different color channel (R, G and B). Also, four classes of aerial images were considered (forest, buildings, grassland and flooding zone). The method of comparison, based on sub-images, average and the Minkovski distance, improves the performance of the texture-based classification. A set of 100 aerial images from UAV was tested for establishing the rate of correct classification.
CITATION STYLE
Popescu, D., & Ichim, L. (2015). Image recognition in UAV application based on texture analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9386, pp. 693–704). Springer Verlag. https://doi.org/10.1007/978-3-319-25903-1_60
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