Content Based Image Retrieval (CBIR) systems represent images in the database
by color, texture, and shape information. In this thesis, we concentrate on tex-
ture features and introduce a new generic texture descriptor, namely, Statistical
Analysis of Structural Information (SASI). Moreover, in order to increase the re-
trieval rates of a CBIR system, we propose a new method that can also adapt an
image retrieval system into a con¯ / gurable one without changing the underlying
feature extraction mechanism and the similarity function.
SASI is based on statistics of clique autocorrelation coe± / cients, calculated
over structuring windows. SASI de¯ / nes a set of clique windows to extract
and measure various structural properties of texture by using a spatial multi-
resolution method. Experimental results, performed on various image databases,
indicate that SASI is more successful then the Gabor Filter descriptors in cap-
turing small granularities and discontinuities such as sharp corners and abrupt
changes. Due to the ° / exibility in designing the clique windows, SASI reaches
higher average retrieval rates compared to Gabor Filter descriptors. However,
the price of this performance is increased computational complexity.
Since, retrieving of similar images of a given query image is a subjective task,
it is desirable that retrieval mechanism should be con¯ / gurable by the user. In the
proposed method, basically, original feature space of a content-based retrieval
system is nonlinearly transformed into a new space, where the distance between
the feature vectors is adjusted by learning. The transformation is realized by
Arti¯ / cial Neural Network architecture. A cost function is de¯ / ned for learning
and optimized by simulated annealing method. Experiments are done on the
texture image retrieval system, which use SASI and Gabor Filter features. The
results indicate that con¯ / gured image retrieval system is signi¯ / cantly better than
the original system.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/4/1035534/index.pdf |
| Date | 01 January 2003 |
| Creators | Carkacioglu, Abdurrahman |
| Contributors | Yarman Vural, Fatos |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | Ph.D. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
Page generated in 0.0119 seconds