Efficient Iris Localization via Optimization Model

Wang, Qi; Liu, Zhipeng; Shu, Tong; Yang, Yuqi; Zhang, Xiangde

doi:10.1155/2017/7952152

Cited by 4 publications

(1 citation statement)

References 21 publications

(26 reference statements)

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“…Daugman's integro-differential operator [6], [7], [8] searches the image domain for the maximum in the blurred partial derivative, concerning the increasing radius r of the normalised contour integral of I(x, y) along with a circular arc ds of radius r and centre coordinates (x 0 , y 0 ). In Eq.…”

Section: Literature Reviewmentioning

confidence: 99%

Fast Iris Localization Based on Image Algebra and Morphological Operations

Hashim¹,

Saleh²

2019

JUBPAS

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The localization of the iris is the most significant factor in biometrics of the iris, which traditionally assumes strictly controlled environments. The proposed method includes the pupillary and limbic iris boundaries localization. A primary advantage of image arithmetic operations is that the process is straightforward and therefore fast, these characteristics are employed and combined with the morphological operators in the designing of the proposed algorithm. The proposed algorithm takes into account the noise area which is found in various parts of the eye image such as light reflections, focus, and small visible iris. The experimental results are conducted on a collection of iris images consist of 756 images belong to Chinese Academy of Sciences Institute of Automation (CASIA V-1) and 450 images belong to Multi Media University (MMU V-1) databases. The results indicate a high level of accuracy using the proposed technique. Moreover, the comparison results with the state-of-the-art iris localization algorithms expose considerable improvement in segmentation accuracy while being computationally more efficient.

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Section: Literature Reviewmentioning

confidence: 99%