Adaptive image classification for aerial photo image retrieval

The paper presents a content based image retrieval approach with adaptive and intelligent image classification through on-line model modification. It supports geographical image retrieval over digitized historical aerial photographs in a digital library. Since the historical aerial photographs are gray-scaled and low-resolution images, image retrieval is achieved on the basis of texture feature extraction. Feature extraction methods for geographical image retrieval are Gabor spectral filtering, Laws' energy filtering, and Wavelet transformation, which are all the most widely used in image classification and segmentation. Adaptive image classification supports effective content based image retrieval through composite classifier models dealing with multi-modal feature distribution. The image retrieval methods presented in the paper are evaluated over a test bed of 184 aerial photographs. The experimental results also show the performance of different feature extraction methods for each image retrieval method.