Search Results - (( iris segmentation matching algorithm ) OR ( java application optimisation algorithm ))

Iris Segmentation Analysis using Integro-Differential Operator and Hough Transform in Biometric System by Zainal Abidin, Zaheera, -, M.Manaf, Shibghatullah, Abdul Samad, -, S.H.A.Mohd Yunos, -, S.Anawar, -, Z.Ayop

“…There are four steps in iris recognition: segmentation,normalization, encoding and matching. …”
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Iris Segmentation Analysis Using Integro-Differential Operator And Hough Transform In Biometric System by Zainal Abidin, Zaheera, Anawar, Syarulnaziah, Ayop, Zakiah, Manaf, Mazani, Shibghatullah, A.S., Mohd Yunos, S.H.A.

“…Iris segmentation is foremost part of iris recognition system.There are four steps in iris recognition: segmentation,normalization,encoding and matching.Here, iris segmentation has been implemented using Hough Transform and IntegroDifferential Operator techniques.The performance of iris recognition system depends on segmentation and normalization technique.Iris recognition systems capture an image from individual eye.Then the image captured is segmented and normalized for encoding process.The matching technique,Hamming Distance,is used to match the iris codes of iris in the database weather it is same with the newly enrolled for verification stage.These processes produce values of average circle pupil,average circle iris,error rate and edge points.The values provide acceptable measures of accuracy False Accept Rate (FAR) or False Reject Rate (FRR).Hough Transform algorithm,provide better performance,at the expense of higher computational complexity.It is used to evolve a contour that can fit to a non-circular iris boundary.However,edge information is required to control the evolution and stopping the contour.The performance of Hough Transform for CASIA database was 80.88% due to the lack of edge information.The GAR value using Hough Transform is 98.9% genuine while 98.6% through Integro-Differential Operator.…”
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DEVELOPMENT OF IRIS RECOGNITION SYSTEM by Mohd Kamarudin, Nur Eliza

“…Iris recognition in this project consist of segmentation, iris normalization, feature extraction, and lastly template matching. …”
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Iris Recognition As Biometric Authentication by Kamaruddin, Muhammad Khairulsyamim

“…In this project, the proposed iris recognition technique will be based on the John Daugman’s algorithm. …”
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Development of efficient iris identification algorithm using wavelet packets for smartphone application by Gunawan, Teddy Surya, Solihin, Nurul Shaieda, Morshidi, Malik Arman, Kartiwi, Mira

“…There are several steps needed in order to recognize the iris which are pre-processing the iris image consists of segmentation and normalization, extract the feature that available in the iris image and identify this image to see whether it match with the person or not. …”
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Model of Bayesian tangent eye shape for eye capture by Nsaef, Asama Kuder, Jaafar, Azizah, Sliman, Layth, Sulaiman, Riza, O. K. Rahmat, Rahmita Wirza

“…In addition, the process of segmentation, normalization and feature extraction is followed by the iris of an eye image in the system. …”
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Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali by M. Ali, Musab A.

“…Hence, the objectives of this research are new algorithms development significantly for iris segmentation specifically the proposed Fusion of Profile and Mask Technique (FPM) specifically in getting the actual center of the pupil with high level of accuracy prior to iris localization task, followed by a particular enhancement in iris normalization that is the application of quarter size of an iris image (instead of processing a whole or half size of an iris image) and for better precision and faster recognition with the robust Support Vector Machine (SVM) as classifier. …”
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Automatic ear recognition under varying illumination / Ali Abd Almisreb by Abd Almisreb, Ali

“…For feature extraction, we used ID log- Gabor filter to generate an ear code and hamming distance is utilized as matching algorithm. Subjective evaluations showed that our proposed system managed to achieve 95% &r ear segmentation rate and 96.662% for ear recognition rate.…”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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