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Aerial Photo Image Retrieval Using Adaptive Image Classification

  • Sung Wook Baik
  • Moon Seok Jeong
  • Ran Baik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4253)

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.

Keywords

Radial Basis Function Image Retrieval Digital Library Image Classification Query Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Sung Wook Baik
    • 1
  • Moon Seok Jeong
    • 1
  • Ran Baik
    • 2
  1. 1.College of Electronics and Information EngineeringSejong UniversitySeoulKorea
  2. 2.Department of Computer EngineeringHonam UniversityGwangjuKorea

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