Abstract
This article proposed a novel human identification method based on retinal images. The proposed system composed of two main parts, feature extraction component and decision-making component. In feature extraction component, first blood vessels extracted and then they have been thinned by a morphological algorithm. Then, two feature vectors are constructed for each image, by utilizing angular and radial partitioning. In previous studies, Manhattan distance has been used as similarity measure between images. In this article, a fuzzy system with Manhattan distances of two feature vectors as input and similarity measure as output has been added to decision-making component. Simulations show that this system is about 99.75% accurate which make it superior to a great extent versus previous studies. In addition to high accuracy rate, rotation invariance and low computational overhead are other advantages of the proposed systems that make it ideal for real-time systems.
Highlights
Biometric is composed of two Greek roots, Bios is meaning life and Metron is meaning measure
Biometrics refers to human identification methods which based on physical or behavioral characteristics
As we stated in feature extraction section, in the proposed system, two feature vectors have been extracted for each image by applying angular and radial partitioning
Summary
Biometric is composed of two Greek roots, Bios is meaning life and Metron is meaning measure. A novel human identification system based on retinal images has been proposed. We extracts feature vectors for all images of our database by utilizing angular and radial partitioning. Retina-based identification and recognition systems have uniqueness and stability properties because pattern of retina’s vessels is unique and stable.
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