Author(s): Wafa Barkhod, Fardin Akhlaqian, Mehran Deljavan Amiri, Mohammad Sadegh Norouzzadeh

Year: 2011

Pub. Info: EURASIP Journal on Advances in Signal Processing

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6 Steps of feature vector extraction in the proposed system. (a) Initial image of the retina. (b) Retina’s image after preprocessing step. (c) Pattern of blood vessels extracted by the algorithm in [13]. (d) Thinned pattern of vessels using a morphological algorithm. (e) Angular portioning. (f) Radial partitioning.

 

 

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 decisionmaking 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.

BibTex: @article{barkhoda2011retina, title={Retina identification based on the pattern of blood vessels using fuzzy logic}, author={Barkhoda, Wafa and Akhlaqian, Fardin and Amiri, Mehran Deljavan and Nouroozzadeh, Mohammad Sadeq}, journal={EURASIP Journal on Advances in Signal Processing}, volume={2011}, number={1}, pages={113}, year={2011}, publisher={Springer} }