• About
  • Policies
  • What is open access
  • Library
  • Contact
Advanced search
      View Item 
      •   BUIR Home
      • University Library
      • Bilkent Theses
      • Theses - Department of Computer Engineering
      • Dept. of Computer Engineering - Master's degree
      • View Item
      •   BUIR Home
      • University Library
      • Bilkent Theses
      • Theses - Department of Computer Engineering
      • Dept. of Computer Engineering - Master's degree
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Image information mining using spatial relationship constraints

      Thumbnail
      View / Download
      62.1 Mb
      Author(s)
      Karakuş, Fatih
      Advisor
      Aksoy, Selim
      Date
      2012
      Publisher
      Bilkent University
      Language
      English
      Type
      Thesis
      Item Usage Stats
      92
      views
      21
      downloads
      Abstract
      There is a huge amount of data which is collected from the Earth observation satellites and they are continuously sending data to Earth receiving stations day by day. Therefore, mining of those data becomes more important for effective processing of collected multi-spectral images. The most popular approaches for this problem use the meta-data of the images such as geographical coordinates etc. However, these approaches do not offer a good solution for determining what those images contain. Some researches make a big step from the meta-data based approaches in this area by moving the focus of the study to content based approaches such as utilizing the region information of the sensed images. In this thesis, we propose a novel, generic and extendable image information mining system that uses spatial relationship constraints. In this system, we use not only the region content, but also relationships of those regions. First, we extract the region information of the images and then extract pairwise relationship information of those regions such as left, right, above, below, near, far and distance etc. This feature extraction process is defined as a generic process which is independent from how the region segmentation is obtained. In addition to these, since new features and new approaches are continuously being developed by the image information mining researchers, extendability feature of the our system plays a big role while we are designing our system. In this thesis, we also propose a novel feature vector structure in which a feature vector consists of several sub-feature vectors. In the proposed feature vector structure, each sub-feature vector can be exclusively selected to be used for search process and they can have different distance metrics to be used in comparisons between the same sub-feature vector of the other feature vector structures. Therefore, the system gives ability to users to choose which information about the region and its pairwise relationship with other regions to be used when they perform a search on the system. The proposed system is illustrated by using region based retrieval scenarios on very high spatial resolution satellite images.
      Keywords
      Image information mining
      Spatial relationships
      Content based image retrieval
      Image databases
      Image retrieval
      Information retrieval
      Remote sensing
      Permalink
      http://hdl.handle.net/11693/15695
      Collections
      • Dept. of Computer Engineering - Master's degree 517
      Show full item record

      Browse

      All of BUIRCommunities & CollectionsTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsThis CollectionTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartments

      My Account

      LoginRegister

      Statistics

      View Usage StatisticsView Google Analytics Statistics

      Bilkent University

      If you have trouble accessing this page and need to request an alternate format, contact the site administrator. Phone: (312) 290 1771
      © Bilkent University - Library IT

      Contact Us | Send Feedback | Off-Campus Access | Admin | Privacy