Article,
Neuro-Fuzzy Based Clustering Approach for Content Based Image Retrieval Using 2DWavelet Transform
International Journal on Signal & Image Processing, 1 (1): 7 (January 2010)
Abstract
In this paper we introduce neuro-fuzzy based
clustering approach for content based image retrieval using
2D-wavelet transform(2D-DWT). Most of the image
retrieval systems are still incapable of providing retrieval
result with high retrieval accuracy and less computational
complexity.To address this problem, we developed neural
network -fuzzy logic cluster based approach for content
based image retrieval using 2D-wavelet transform. The
system performance improved by the learning and
searching capability of the neural network combined with
the fuzzy interpretation. This overcomes the vagueness and
inconsistency due to human subjectivity. Multiresolution
analysis using 2D-DWT can decompose the image into
components at different scales, so that the coarest scale
components carry the global approximation information
while the finer scale components contain the detailed
information. The empirical results show that the precision
improved from 78% to 98% and average recall rate of 77%
to 98% for the general purpose database size of 10000
images compared with other existing approaches.
