TELKOMNIKA Telecommunication Computing Electronics and Control
Enhance iris segmentation method for person recognition based on image processing techniques
Dublin Core
Title
TELKOMNIKA Telecommunication Computing Electronics and Control
Enhance iris segmentation method for person recognition based on image processing techniques
Enhance iris segmentation method for person recognition based on image processing techniques
Subject
Biometrics
Canny edge detection
Hough transform
Iris recognition
Iris segmentation
Canny edge detection
Hough transform
Iris recognition
Iris segmentation
Description
The limitation of traditional iris recognition systems to process iris images
captured in unconstraint environments is a breakthrough. Automatic iris
recognition has to face unpredictable variations of iris images in real-world
applications. For example, the most challenging problems are related to the
severe noise effects that are inherent to these unconstrained iris recognition
systems, varying illumination, obstruction of the upper or lower eyelids, the
eyelash overlap with the iris region, specular highlights on pupils which
come from a spot of light during captured the image, and decentralization of
iris image which caused by the person’s gaze. Iris segmentation is one of the
most important processes in iris recognition. Due to the different types of
noise in the eye image, the segmentation result may be erroneous. To solve
this problem, this paper develops an efficient iris segmentation algorithm
using image processing techniques. Firstly, the outer boundary segmentation
of the iris problem is solved. Then the pupil boundary is detected. Testes are
done on the Chinese Academy of Sciences’ Institute of Automation
(CASIA) database. Experimental results indicate that the proposed algorithm
is efficient and effective in terms of iris segmentation and reduction of time
processing. The accuracy results for both datasets (CASIA-V1 and V4) are
100% and 99.16 respectively.
captured in unconstraint environments is a breakthrough. Automatic iris
recognition has to face unpredictable variations of iris images in real-world
applications. For example, the most challenging problems are related to the
severe noise effects that are inherent to these unconstrained iris recognition
systems, varying illumination, obstruction of the upper or lower eyelids, the
eyelash overlap with the iris region, specular highlights on pupils which
come from a spot of light during captured the image, and decentralization of
iris image which caused by the person’s gaze. Iris segmentation is one of the
most important processes in iris recognition. Due to the different types of
noise in the eye image, the segmentation result may be erroneous. To solve
this problem, this paper develops an efficient iris segmentation algorithm
using image processing techniques. Firstly, the outer boundary segmentation
of the iris problem is solved. Then the pupil boundary is detected. Testes are
done on the Chinese Academy of Sciences’ Institute of Automation
(CASIA) database. Experimental results indicate that the proposed algorithm
is efficient and effective in terms of iris segmentation and reduction of time
processing. The accuracy results for both datasets (CASIA-V1 and V4) are
100% and 99.16 respectively.
Creator
Israa A. Hassan, Suhad A. Ali, Hadab Khalid Obayes
Source
http://telkomnika.uad.ac.id
Date
Oct 26, 2022
Contributor
peri irawan
Format
pdf
Language
english
Type
text
Files
Collection
Citation
Israa A. Hassan, Suhad A. Ali, Hadab Khalid Obayes, “TELKOMNIKA Telecommunication Computing Electronics and Control
Enhance iris segmentation method for person recognition based on image processing techniques,” Repository Horizon University Indonesia, accessed November 22, 2024, https://repository.horizon.ac.id/items/show/4496.
Enhance iris segmentation method for person recognition based on image processing techniques,” Repository Horizon University Indonesia, accessed November 22, 2024, https://repository.horizon.ac.id/items/show/4496.