An automatic system of detecting changes in aerial images using ANN based contourlet transform

The obtaining of the aerial images got easy thanks to technological developments in the field of unmanned aerial vehicles and these images were began to be used frequently in the field of image processing. Automatic changes detection from aerial images is among the most important study fields. An automatic system for changes detection has been proposed by using contourlet transform and artificial neural network (ANN) in this study. The contourlet transform is applied to the reference image in the first phase of the system consisting of two phases. Mean, variance, standard deviation and skewness values were calculated from the obtained sub-image matrix and seven image feature vectors are formed by using these statistical values and combinations. The numerical equivalents of the reference image were obtained by using the feature vectors by ANN. The same procedures were applied to the image that its exchange will be examined in the second phase of the system. The change between numerical provisions of the reference image and the image to be examined compared to the threshold value set by the user and automatic changes detection was performed. It was found that the changes in numerical results obtained at the end of the study overlap with the changes in aerial images.