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Research Article Open Access
In this paper presented an, intellectual methodology for automation in segmentation and semantic annotation of Synthetic Aperture Radar (SAR) images. A hybrid, artificial neural network based combination of region connection calculus (RCC) and fractal JSEG algorithm was used to segment the spatially oriented SAR images. Ontological approach was used to semantically annotate the notable regions on the segmented SAR images. For the automatic tagging of images, shape based contour gradient algorithm were proposed and used effectively. The contour gradient feature for the region like road, irrigation land, building, water reservoirs and etc., are extracted and the values are indexed respectively in the created ontology. The experimental results show promising gain on the annotation of untrained SAR images.
SAR images, RCC, Ontology, JSEG, Segmentation, Artificial neural network, #