Pengenalan Iris menggunakan Ekstraksi Fitur Histogram of Oriented Gradient

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Siska Devella

Abstract

Iris is a biometric-based on physiological characteristics. Iris is completely unique, the patterns of one person's two eyes are quite different from each other and even genetically identical twins have different iris patterns. The Iris of a person is stable throughout a person's life. Therefore, the iris recognition system has a high level of security. This study proposed iris recognition system using Histogram of Oriented Gradient (HOG) as feature extraction and two classifier K - Nearest Neighbors (K-NN) and Naive Bayes. CASIA Iris Interval V4.0 database is utilized to evaluate the performance of the proposed methods. The experimental results show that the iris image with normalization has a better accuracy when compared with iris images without normalization. The highest accuracy in this research is HOG + KNN for iris with normalization, with accuracy 96%.

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How to Cite
Devella, S. (2018). Pengenalan Iris menggunakan Ekstraksi Fitur Histogram of Oriented Gradient. Jurnal Teknik Informatika Dan Sistem Informasi, 4(1), 124 -. Retrieved from https://journal.maranatha.edu/index.php/jutisi/article/view/1515
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