The principal purpose of the CBIR system is to
construct meaningful descriptions of physical attributes
from images. Physical features and mathematical features
are two such typical descriptions. Many research efforts
have been made to extract physical features such as color,
texture, edge, structure or a combination of two or more.
The best part of the proposed solutions are variations of the
color histogram initially proposed for object recognition.
Since color histogram lacked spatial information these
methods were liable to produce false positives especially
when the database was large. We proposed a method called
image retrieval using interactive genetic algorithm (IRIGA)
for computing a very large number of highly selective
features and comparing these features for some relevant
images and using only those selected features which
incarcerate similarity in the given relevant images for image
retrieval. Experiments on a collection of 10000 generalpurpose
images reveal the effectiveness of the proposed
framework.
Mrs.K.ValliMadhavi : received her MCA degree in Andhra University,
in 2003, and M.Tech (IT) from Karnataka University, Karnataka in
2010.She is working towards her Ph.D at Dravidian University, She is
with Godavari Institute of Engineering & Technology, A.P as an
Associate Professor. She has 13 Years of experience in teaching
undergraduate students and post graduate students. Her research
benefit are in the areas of image processing, content based image
retrieval, Data warehousing & Mining and cloud computing. She is a
life member in ISCA, CSI (Computer Society of India and Red Cross
Society.
Mrs.R.Tamilkodi : received her MCA degree in Bharathidasan
University, Trichy, in 2002, and M.Tech (IT) from Karnataka
University, Karnataka in 2010.She is working towards her Ph.D at
SaveethaUniversity, She is with Godavari Institute of Engineering &
Technology, A.P as an Associate Professor. She has 11 Years of
experience in teaching undergraduate students and post graduate
students. Her research interests are in the areas of image
processing, content based image retrieval and cloud computing. She
is a life member in ISCA and Red Cross Society.
This paper has presented top ranked images to be
retrieved in interactive CBIR system. In contrast to
conventional approaches that are based on visual features,
our method (IRIGA) provides an interactive mechanism
to bridge the gap between the visual features and the
human perception. In addition, the entropy based on the
DWT method is considered as texture descriptors to help
characterize the images. Experimental results of the
projected approach have shown the noteworthy
development in retrieval recital. Further work considering
more low-level image descriptors or high-level semantics
in the future approach is in progress.
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