An application of ant colony algorithm for edge feature extraction in city aerial image for building recognition

Over the years, automatic and semiautomatic extraction of building from aerial and spatial images has become an outstanding issue. This paper presents an application of Ant Colony Algorithm (ACA) for edge extraction in city aerial image for building recognition. The overall idea of this work is clustering pixels by a character complex of gray value, gradient and neighborhood of each pixel. Die results of ACA will be compared with the results of Canny operator which is considered as the best edge feature extracting operator. And the comparison indicated that ACA is efficient in edge feature extraction, especially for the aerial images.