Gender Classification Based on Iris Recognition Using Artificial Neural Networks
Biometric authentication is one of the most quickly increasing innovations in today's world; this promising technology has seen widespread use in a variety of fields, including surveillance services, safe financial transfers, credit-card authentication. in biometric verification processes such...
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| Format: | Article |
| Language: | English |
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Qubahan
2021-05-01
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| Series: | Qubahan Academic Journal |
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| Online Access: | https://journal.qubahan.com/index.php/qaj/article/view/63 |
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| author | Basna Mohammed Salih Adnan Mohsin Abdulazeez Omer Mohammed Salih Hassan |
| author_facet | Basna Mohammed Salih Adnan Mohsin Abdulazeez Omer Mohammed Salih Hassan |
| author_sort | Basna Mohammed Salih |
| collection | DOAJ |
| description |
Biometric authentication is one of the most quickly increasing innovations in today's world; this promising technology has seen widespread use in a variety of fields, including surveillance services, safe financial transfers, credit-card authentication. in biometric verification processes such as gender, age, ethnicity is iris recognition technology is considered the most accurate compared to other vital features such as face, hand geometry, and fingerprints. Because the irises in the same person are not similar. In this work, the study of gender classification using Artificial Neural Networks (ANN) based on iris recognition. The eye image data were collected from the IIT Delhi IRIS Database. All datasets of images were processed using various image processing techniques using the neural network. The results obtained showed high performance in training and got good results in testing. ANN's training and testing process gave a maximum performance at 96.4% and 97% respectively.
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| format | Article |
| id | doaj-art-9084ab9fafa34965bf6d6cba5b33a45b |
| institution | Kabale University |
| issn | 2709-8206 |
| language | English |
| publishDate | 2021-05-01 |
| publisher | Qubahan |
| record_format | Article |
| series | Qubahan Academic Journal |
| spelling | doaj-art-9084ab9fafa34965bf6d6cba5b33a45b2025-02-03T10:12:48ZengQubahanQubahan Academic Journal2709-82062021-05-011210.48161/qaj.v1n2a6363Gender Classification Based on Iris Recognition Using Artificial Neural Networks Basna Mohammed Salih0Adnan Mohsin Abdulazeez1Omer Mohammed Salih Hassan2Technical College of Informatics Akre, Duhok Polytechnic University Duhok, IraqResearch Center Duhok Polytechnic University Duhok, IraqResearch Center Duhok Polytechnic University, Duhok, Iraq Biometric authentication is one of the most quickly increasing innovations in today's world; this promising technology has seen widespread use in a variety of fields, including surveillance services, safe financial transfers, credit-card authentication. in biometric verification processes such as gender, age, ethnicity is iris recognition technology is considered the most accurate compared to other vital features such as face, hand geometry, and fingerprints. Because the irises in the same person are not similar. In this work, the study of gender classification using Artificial Neural Networks (ANN) based on iris recognition. The eye image data were collected from the IIT Delhi IRIS Database. All datasets of images were processed using various image processing techniques using the neural network. The results obtained showed high performance in training and got good results in testing. ANN's training and testing process gave a maximum performance at 96.4% and 97% respectively. https://journal.qubahan.com/index.php/qaj/article/view/63Gender prediction, Iris biometrics, Artificial Neural Networks, Canny Edge Detection. |
| spellingShingle | Basna Mohammed Salih Adnan Mohsin Abdulazeez Omer Mohammed Salih Hassan Gender Classification Based on Iris Recognition Using Artificial Neural Networks Qubahan Academic Journal Gender prediction, Iris biometrics, Artificial Neural Networks, Canny Edge Detection. |
| title | Gender Classification Based on Iris Recognition Using Artificial Neural Networks |
| title_full | Gender Classification Based on Iris Recognition Using Artificial Neural Networks |
| title_fullStr | Gender Classification Based on Iris Recognition Using Artificial Neural Networks |
| title_full_unstemmed | Gender Classification Based on Iris Recognition Using Artificial Neural Networks |
| title_short | Gender Classification Based on Iris Recognition Using Artificial Neural Networks |
| title_sort | gender classification based on iris recognition using artificial neural networks |
| topic | Gender prediction, Iris biometrics, Artificial Neural Networks, Canny Edge Detection. |
| url | https://journal.qubahan.com/index.php/qaj/article/view/63 |
| work_keys_str_mv | AT basnamohammedsalih genderclassificationbasedonirisrecognitionusingartificialneuralnetworks AT adnanmohsinabdulazeez genderclassificationbasedonirisrecognitionusingartificialneuralnetworks AT omermohammedsalihhassan genderclassificationbasedonirisrecognitionusingartificialneuralnetworks |