Updation of cartographical database with the aid of different traits in blending of ANN and ANFIS

In recent years, the image processing plays a major role in real world and that are utilized in many of the application domains. Besides the other, in the field of remote sensing the contribution of images is thunderstruck. Nowadays, a wide number of buildings are updated often; this can be updated in the cartographical database which is comprised of remote sensing images of buildings. Updating cartographic database is an important process in order to identify the new buildings and roads. In this work, the high resolution satellite images are utilized to identify the updated buildings. For this process, images of different time period is utilized and then the traits are identified; here the traits are building, road and vegetation. For this intention, the Artificial Neural Network (ANN) is designed separately for each of them. Once the traits are identified from both images of different time period, then the unique traits are identified. Prior to this process, with the aid of the ANFIS the each region wise traits are trained. Subsequently, the uniquely identified traits are evaluated in this ANFIS in order to identify whether the trait is building or not. Once the building is identified, then it is marked in the original image and then the image is utilized to update in the cartographical database.