Search Results - (( iris segmentation matching algorithm ) OR ( java application optimized algorithm ))
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Iris Segmentation Analysis using Integro-Differential Operator and Hough Transform in Biometric System
Published 2012“…There are four steps in iris recognition: segmentation,normalization, encoding and matching. …”
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Article -
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Iris Segmentation Analysis Using Integro-Differential Operator And Hough Transform In Biometric System
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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DEVELOPMENT OF IRIS RECOGNITION SYSTEM
Published 2016“…Iris recognition in this project consist of segmentation, iris normalization, feature extraction, and lastly template matching. …”
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Final Year Project -
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Iris Recognition As Biometric Authentication
Published 2016“…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
Published 2017“…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
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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Conference or Workshop Item -
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Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
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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Thesis -
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Automatic ear recognition under varying illumination / Ali Abd Almisreb
Published 2012“…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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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Ant colony optimization algorithm for load balancing in grid computing
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Improving Class Timetabling using Genetic Algorithm
Published 2006“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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