Semi-automatic Extraction of Features from Digital Imagery

Aerial photographs have been evaluated manually by the operators for a long time for the extraction of the vector data. The development of computer technology and digital image processing technologies provide to perform these extraction processes automatically or semi-automatically. Image segmentation can be used for automatic and semi-automatic feature extraction and classification of images. In recent years, image segmentation and the front propagation of the segments have been carried out successfully by the Level Set and Fast Marching methods. In this study, a semi-automatic line extraction method, based on the segmentation of the images using color-differences of the pixels and the propagation of the fronts by the Level Set algorithms, is developed. An object oriented application software is also developed to test the capabilities of the developed method. Some semiautomatic feature extraction applications are made by the help of the developed software using a 1:16000 scale black/white aerial photograph for determining the capabilities of this method. Another application with 1:5000 scaled two ortho images which have 0.50m resolution. These ortho images are generated from 1:16000 scale color aerial photographs. In this test area, an accuracy test is also carried out to find the accuracy of the developed method. The accuracy test is carried out in two groups. In the first group, on 422 road check points, measurements are made and the root square mean is found as ±0.66m. In the second group, buildings are used and 281 check points are measured and the root mean square of this group is found as ±0.46m. * Corresponding author.