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- W2421366796 abstract "The aim of this work is to improve the performance of iris recognition systems by using hyperspectral iris images. The commercial iris recognition systems that already exist mostly use the information of iris in the infrared band and the performance of these systems more often depends on segmentation process. Thus, in this work, more reliable and effective segmentation is attempted by utilizing iris information in visible and infrared bands. The dataset that includes iris images of 17 people in 16 different wavelengths is used. The circular Hough transform is used to detect the region of the iris. K-nearest neighbors (K-NN) algorithm is preferred to use the hyperspectral data information in different bands. As a result of these methods, segmentation is made with 84% success rate." @default.
- W2421366796 created "2016-06-24" @default.
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- W2421366796 date "2016-05-01" @default.
- W2421366796 modified "2023-10-17" @default.
- W2421366796 title "Iris segmentation with using hyperspektral images" @default.
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- W2421366796 doi "https://doi.org/10.1109/siu.2016.7495934" @default.
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