IRIS recognition system using MATLAB

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dc.contributor.author Kotiyal, Bandanawaz
dc.contributor.author Kazmi, Md. Nasrullah (14DET50)
dc.contributor.author Faiz, Mohd (12ET77)
dc.date.accessioned 2017-05-19T06:00:55Z
dc.date.available 2017-05-19T06:00:55Z
dc.date.issued 2017-05
dc.identifier.uri http://www.aiktcdspace.org:8080/jspui/handle/123456789/1964
dc.description.abstract Individual recognition using Iris is most commonly employed in all place. This requires some special cameras to take the Iris image and the obtained iris images were classified based on the features extracted. Only identification of person is not the application of Iris recognition. It can be developed to do many process.The iris image captured from the cameras were taken. Individual recognition using Iris is most commonly employed in all place. In the proposed approach the process of recognition of the persons based on Iris image is employed. The recognition of iris is done based on the DWT features extracted from iris image. The DWT features were the statistical features extracted from the input images. The extracted features were optimized based on Genetic algorithm. The genetic algorithm process includes selection, crossover and mutation process. The probability of the selection of the features were estimated in the selection, cross over and the mutation process. The optimized features were then used for matching process based on Euclidean distance measurement. Before the extraction of the features preprocessing in the iris images were employed based on the smoothening process and the edge detection process. The preprocessed iris image is then normalized. The normalization process identifies the iris and pupil region in the image correctly and it reshapes the identified positions. The normalization process improves the efficiency. The process of application of the optimization techniques helps in the reduction of the feature counting. The person to whom the input iris belongs is identified and with the help of the identified person the matching process is employed. The performance of the process is measured based on the performance metrics. The performance of the process measured indicates that the proposed approach is more improved compared to the other existing approaches for the iris recognition process. en_US
dc.language.iso en_US en_US
dc.publisher AIKTC en_US
dc.relation.ispartofseries Accession # PE0176;
dc.subject Project Report - EXTC en_US
dc.title IRIS recognition system using MATLAB en_US
dc.type Project Report en_US


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