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(searched for: A-MATLAB-based-Convolutional-Neural-Network-Approach-for-Face-Recognition-System)
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International Journal of Recent Technology and Engineering, Volume 8, pp 2116-2124; doi:10.35940/ijrte.b2332.078219

Abstract: Today’s most of the iris
recognition
systems
are strongly dependent on user’s cooperation during image acquisition such as stop-stair condition, head position and camera distance. Images are taken in NIR spectrum to reduce the noise such as effect of illumination. Challenges
faced
by existing iris
recognition
systems
are such as they are time consuming due to need of extra hardware setup and unable to achieve better performance
for
images acquired on-the-move, at-
a
-distance, etc.. To overcome these challenges, in this paper we proposed novel segmentation algorithm
based
on content
based
image retrieval
approach
. In proposed segmentation method, color, texture and brightness contour features were extracted. Entropy value
for
these extracted contour features was measured to reduce the dimensionality of features. These set of calculated entropy value was given as input to
convolutional
neural
network
to cluster noisy eye image into iris, sclera and pupil region. The proposed segmentation algorithm was experimented on freely available UBIRIS.V2 noisy eye image database using
MATLAB
. The experimentation results shows that proposed segmentation method is superior as compared to existing method by reducing average segmentation time up to 0.9sec and increasing segmentation accuracy up to 97%
for
non ideal color eye images.
Sciprofile link
A
. R. Syafeeza
, Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Malacca, Malaysia
Journal of Bioinformatics and Proteomics Review, Volume 2, pp 1-5; doi:10.15436/2381-0793.16.009

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