Hybrid clusteing algorithm and Neural Network classifier for satellite image classification

This paper presents a hybrid clustering algorithm and feed-forward neural network classifier for land-cover mapping of trees, shade, building and road. It starts with the single step preprocessing procedure to make the image suitable for segmentation. The preprocessed image is segmented using the hybrid genetic-Artificial Bee Colony (ABC) algorithm that is developed by hybridizing the ABC and FCM to obtain the effective segmentation in satellite image and classified using neural network. The performance of the proposed hybrid algorithm is compared with the algorithms like, Artificial Bee Colony(ABC) algorithm, ABC-GA algorithm, Moving KFCM.