Search Results - (( java implementation developing algorithm ) OR ( iris segmentation _ algorithm ))

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  1. 1
    Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images

    Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images by Jamaludin, Shahrizan, Mohamad Ayob, Ahmad Faisal, Mohd Norzeli, Syamimi, Mohamed, Saiful Bahri

    Published 2022
    “…This algorithm is significant to solve inaccurate segmentation on blurry iris images.…”
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  2. 2
    Black hole algorithm along edge detector and circular hough transform based iris projection with biometric identification systems

    Black hole algorithm along edge detector and circular hough transform based iris projection with biometric identification systems by Tara Othman Qadir, Tara Othman Qadir, N.S.A.M Taujuddin, N.S.A.M Taujuddin

    Published 2024
    “…In this study, we presented a Black Hole Algorithm (BHA) along the Canny edge detector and circular Hough transform-based optimization technique for circular parameter identification of iris segmentation. …”
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  3. 3
    DEVELOPMENT OF IRIS RECOGNITION SYSTEM

    DEVELOPMENT OF IRIS RECOGNITION SYSTEM by Mohd Kamarudin, Nur Eliza

    Published 2016
    “…Hough transform method is used in iris segmentation to detect location of iris and pupil region in the image. …”
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  4. 4
    Iris segmentation and normalization approach

    Iris segmentation and normalization approach by Shamsi, Mahboubeh, Saad, Puteh, Rasouli, Abdolreza

    Published 2008
    “…The algorithm is tested using iris images from CASIA database and MMU database. …”
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  5. 5
    Iris Segmentation Analysis using Integro-Differential Operator and Hough Transform in Biometric System

    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

    Published 2012
    “…Iris segmentation is foremost part of iris recognition system. …”
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  6. 6
    Iris Segmentation Analysis Using Integro-Differential Operator And Hough Transform In Biometric System

    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.

    Published 2012
    “…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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  7. 7
    Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation

    Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation by Mat Ibrahim, Masrullizam, Awang Md Isa, Azmi, Darsono, Abd Majid

    Published 2014
    “…Eye closure detection is an important operation prior to carry out the main algorithm such as iris recognition algorithms, and eye tracking algorithms. …”
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  8. 8
    Spot Filtering Adaptive Thresholding (SFAT) Method for iris pigment spots segmentation approach / Mustafa Man ... [et al.]

    Spot Filtering Adaptive Thresholding (SFAT) Method for iris pigment spots segmentation approach / Mustafa Man ... [et al.] by Man, Mustafa, Ab Jabal, Mohamad Faizal, Wan Yussof, Wan Nural Jawahir, Hamid, Suhardi, Mohd Rahim, Mohd Shafry

    Published 2018
    “…The result achieved from the testing is 37.02% of the accuracy on the segmentation of the iris pigment spots on the iris surface. …”
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  9. 9
    An efficient iris image thresholding based on binarization threshold in black hole search method

    An efficient iris image thresholding based on binarization threshold in black hole search method by Danlami, Muktar, Ramli, Sofia Najwa, Jemain, Nur Izzah Syahira, Pindar, Zahraddeen, Jamel, Sapiee, Deris, Mustafa Mat

    Published 2018
    “…Several algorithms have been proposed in order to segment the outer and lower boundary of the iris region. …”
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  10. 10
    Development of efficient iris identification algorithm using wavelet packets for smartphone application

    Development of efficient iris identification algorithm using wavelet packets for smartphone application by Gunawan, Teddy Surya, Solihin, Nurul Shaieda, Morshidi, Malik Arman, Kartiwi, Mira

    Published 2017
    “…Performance of the proposed algorithm was tested on Chinese Academy of Sciences Institute of Automation (CASIA) iris image database. …”
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  11. 11
    Iris Recognition As Biometric Authentication

    Iris Recognition As Biometric Authentication by Kamaruddin, Muhammad Khairulsyamim

    Published 2016
    “…In this project, the proposed iris recognition technique will be based on the John Daugman’s algorithm. …”
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  12. 12
    Feature Extraction From Epigenetic Traits Using Edge Detection In Iris Recognition System

    Feature Extraction From Epigenetic Traits Using Edge Detection In Iris Recognition System by Zainal Abidin, Zaheera, Manaf, Mazani, Shibghatullah, Abdul Samad

    Published 2013
    “…Most iris recognition systems use algorithms developed by Daugman. …”
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  13. 13
    Detection of corneal arcus using rubber sheet and machine learning methods

    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The segmentation iris is transformed to rectangular shape using the Rubber Sheet method. …”
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  14. 14
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
    “…The library is implemented by using Java cryptographic service provider framework that conforms to Java Cryptographic Architecture (JCA) and Java Cryptographic Extension (JCE). …”
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  15. 15
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  16. 16
    Biometric identification and recognition for IRIS using Failure Rejection Rate (FRR) / Musab Ahmed Mohammed Ali Al-Rawi

    Biometric identification and recognition for IRIS using Failure Rejection Rate (FRR) / Musab Ahmed Mohammed Ali Al-Rawi by Mohammed Ali Al-Rawi, Musab Ahmed

    Published 2016
    “…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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  17. 17
    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING

    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

    Published 2021
    “…RSA is one of these encryption algorithms that have been implemented in security systems. …”
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  18. 18
    Model of Bayesian tangent eye shape for eye capture

    Model of Bayesian tangent eye shape for eye capture by Nsaef, Asama Kuder, Jaafar, Azizah, Sliman, Layth, Sulaiman, Riza, O. K. Rahmat, Rahmita Wirza

    Published 2014
    “…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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  19. 19
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  20. 20
    Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali

    Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali by M. Ali, Musab A.

    Published 2016
    “…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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