Image information mining using spatial relationship constraints
Author(s)
Advisor
Date
2012Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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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 miningSpatial relationships
Content based image retrieval
Image databases
Image retrieval
Information retrieval
Remote sensing