Generation of Fake Iris Images Using CycleGAN
Autor: | Gyeyoung Kim, Jae-gab Choi, Jin-Ho Park |
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Rok vydání: | 2021 |
Předmět: |
Palm print
Biometrics urogenital system business.industry Computer science fungi Iris recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Iris detection urologic and male genital diseases Iris flower data set female genital diseases and pregnancy complications ComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMS Identification (information) ComputingMethodologies_PATTERNRECOGNITION medicine.anatomical_structure Fingerprint medicine Computer vision cardiovascular diseases Artificial intelligence Iris (anatomy) business ComputingMethodologies_COMPUTERGRAPHICS |
Zdroj: | Advances in Computer Science and Ubiquitous Computing ISBN: 9789811593420 |
Popis: | With the development of biometric recognition technology, identification of users through biometric information such as iris, fingerprint, and palm print is being applied to many areas. In the case of iris, various methods of recognition and methods of detection of fake iris have been studied at the iris recognition stage. However, fake iris detection research has been conducted by using the printed output or the artificial iris due to the absence of fake iris data. In this paper, fake iris images are generated for the research of the detection of fake iris using CycleGAN. The CycleGAN model has learned to reduce constraints against existing generation models and to avoid bias in probability distributions using bidirectional LossFunction. In the experiment, CASIA Iris Image Database ver 4.0 was used and the data was obtained for the detection of fake iris by creating fake iris. |
Databáze: | OpenAIRE |
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