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already been extensively used in texture image
retrieval literature (Do et al., 2002) (Kokare, 2005)
(Huajing et al., 2008) (Kwitt et al., 2010). The
512x512 pixels colour versions of the textures are
divided into 16 nonoverlapping subimages (128x128
pixels) and converted to gray scale images, thus
creating a database of 640 images belonging to 40
class textures, each class with 16 different samples.
In retrieval experiments, a query image is each
one of 640 images in our database. The relevant
images for each query are all the subimages from the
same original texture. We use the average retrieval
rate (ARR) to evaluate the performance. For a given
query image, the retrieval rate is defined as the
percentage of the number of correct texture images
retrieved in the same class as the query texture
observed in the total number of retrieved images.
For comparison purpose, we retrieve 16 images for
each query. We use every subimage in the database
as query to do retrieval and get the average retrieval
rate finally.
Table 2 provides a quantized comparison. RCWF
indicates Rotated Complex Wavelet Filters method
proposed in (Kokare, 2005). CWT represents the
Complex Wavelet Transform method presented in
(Kingsbury et al., 1999). CWT+RCWF is also
presented in (Kokare, 2005). PTR (Kwitt, 2010) is a
probabilistic texture retrieval method based on dual-
tree complex wavelet transform. It can be observed
that our proposal outperforms other methods.
Table 2: Comparison of ARR with other methods.
Method RCWF CWT PTR CWT+RCWF Proposal
ARR(%) 75.78 80.78 81.73 82.34 83.64
4 CONCLUSIONS
In this paper we have presented a simple and
effective approach for constructing descriptor using
2D DCT coefficients intended to image retrieval.
Unlike other CBIR methods that usually focus on
one kind of image database, our approach is suitable
for different kind of image database. We evaluate
our method both in widely used face database and
texture database. From the point of view of
recognition rate or average retrieval rate, the
experimental results show higher performance
compared to classical and state-of-art methods.
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