Iris recognition by artificial Elman neural network

Abstract<br /> Iris recognition is regarded as the most reliable and accurate biometric identification system available. A biometric system provides automatic identification of an individual based on a unique feature or stable characteristic possessed by the individual. <br /> This resea...

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Main Author: Mawdah Suleiman (Author)
Format: Book
Published: College of Education for Pure Sciences, 2012-12-01T00:00:00Z.
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100 1 0 |a Mawdah Suleiman  |e author 
245 0 0 |a Iris recognition by artificial Elman neural network 
260 |b College of Education for Pure Sciences,   |c 2012-12-01T00:00:00Z. 
500 |a 1812-125X 
500 |a 2664-2530 
500 |a 10.33899/edusj.2012.70981 
520 |a Abstract<br /> Iris recognition is regarded as the most reliable and accurate biometric identification system available. A biometric system provides automatic identification of an individual based on a unique feature or stable characteristic possessed by the individual. <br /> This research involves intelligent iris recognition system. For determination of the recognition performance of the iris, CASIA database of digital grayscale eye image was used. This database was then used to process the illumination which is the most important problem in iris recognition. (42) images for different irises used for training, obtained from CASIA, by extension (bmp), and (30) other snapshots for the same irises for testing because CASIA database provided more than one snapshot for each iris, the feature extraction implemented depended on extract the statistical values of (variance, standard deviation, skweness, kurtosis) and seven invariant moments for each image, the results of simulations of Elman artificial neural network that possessed dynamic memory which used as a tool to take decision, illustrate the effectiveness recognition in training 100% and in testing recognition accuracy = (93.33%). The software to perform iris recognition uses Matlab® (2010) development environment. 
546 |a AR 
546 |a EN 
690 |a iris 
690 |a recognition 
690 |a artificial 
690 |a neural network 
690 |a elman 
690 |a Education 
690 |a L 
690 |a Science (General) 
690 |a Q1-390 
655 7 |a article  |2 local 
786 0 |n مجلة التربية والعلم, Vol 25, Iss 4, Pp 162-182 (2012) 
787 0 |n https://edusj.mosuljournals.com/article_70981_da3fca490efc55090a0e083e9cdc1388.pdf 
787 0 |n https://doaj.org/toc/1812-125X 
787 0 |n https://doaj.org/toc/2664-2530 
856 4 1 |u https://doaj.org/article/958546c7e758414fadd6eeaa38840025  |z Connect to this object online.