This paper presents a new method fast and robust for eyes
detection, using Pulse-Coupled Neural Networks (PCNN). The
functionality is not the same as traditional neural network
because there are no training steps. Due of this feature, the
algorithm response time is around tree millisecond. The
approach has two components including: face area detection
based on segmentation and eyes detection using edge. The both
operations are ensured by PCNN The biggest region which is
constituted by pixel value one will be the human face area. The
segmented face zone which will be the input of PCNN for edge
detection undergoes a vertical gradient operation. The two
gravity’s center of close edge near the horizontal line which
corresponds to the peak value of horizontal projection of vertical
gradient image will be the eyes.
Published In : IJCSN Journal Volume 2, Issue 5
Date of Publication : 01 October 2013
Pages : 11 - 18
Figures : 21
Tables : 02
Publication Link : ijcsn.org/IJCSN-2013/2-5/IJCSN-2013-2-5-21.pdf
Maminiaina A. Rafidison : was born in Moramanga, Madagascar on
1984. He received his Engineer Diploma in Telecommunication on
2007 and M.Sc. on 2011 at High School Polytechnic of Antananarivo,
Madagascar. Currently, he is a consultant expert on Value Added
Service (VAS) in telecom domain at Mahindra Comviva Technologies
and in parallel; he is a Ph.D. student at High School Polytechnic of
Antananarivo. His current research is regarding image processing
especially using Neural Networks.
Andry A. Randriamitantsoa : received his Engineer Diploma in
Telecommunication on 2008 at High School Polytechnic of
Antananarivo, Madagascar and his M.Sc. on 2009. Currently he is
working for High School Polytechnic and he had a PhD in Automatic
and Computer Science in 2013. His research interests include
Automatic, robust command, computer science.
Paul A. Randriamitantsoa : was born in Madagascar on 1953. He is
a professor at High School Polytechnic of Antananarivo and first
responsible of Telecommunication- Automatic – Signal – Image
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Department of Informatics, Aristotle University of
Thessaloniki, Box 451, 54124, Thessaloniki, Greece,