Aerial photo image retrieval using adaptive image classification

Authors:
Sung Wook Baik;Moon Seok Jeong;Ran Baik
Affiliations:
College of Electronics and Information Engineering, Sejong University, Seoul, Korea;College of Electronics and Information Engineering, Sejong University, Seoul, Korea;Department of Computer Engineering, Honam University, Gwangju, Korea
Venue:
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Year:
2006

Citing 6
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Abstract

The paper presents a method for content based image retrieval (CBIR) using an adaptive image classification with Radial Basis Function networks. It supports geographical image retrieval over digitized historical aerial photographs, in a digital library, which are gray-scaled and low-resolution images. CBIR is achieved on the basis of texture feature extraction and image classification. Feature extraction methods for geographical image analysis are Gabor spectral filtering and Laws' energy filtering, which are the most widely used in image classification and segmentation. Image classification supports effective CBIR through composite classifier models dealing with multi-modal feature distribution. The method is evaluated over a digital library that contains collections of thousands of small-sized texture tiles obtained from large-sized aerial photograph images with geographical features.