Iris localization using gradient magnitude and fourier descriptor

Sentanoe, Stewart; Nugroho, Anto Satriyo; Galinium, Maulahikmah; Hartono, Reggio N.; Uliniansyah, Mohammad Teduh; Layooari, Meidy

doi:10.1109/icacsis.2014.7065846

Cited by 1 publication

(10 citation statements)

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“…As stated in Section 2, this research is an enhancement of our previous studies [3] and [7]. Figure 1 shows a scheme of the multimodal biometrics fusion between iris recognition and fingerprint recognition.…”

Section: Proposed Methodsmentioning

confidence: 83%

“…For this reason, Sentanoe [3] have tried to improved Valentina's [7] iris segmentation module by implementing the geodesic active contour algorithm as suggested by Ross and Shah [5]. Sentanoe proposed a circular gradient magnitude and Fourier descriptor algorithm to segment the iris.…”

Section: Related Workmentioning

confidence: 99%

“…The proposed segmentation module uses the same technique as the one developed by Sentanoe [3] with some rule-based improvements, especially in the initial point localization step. Figure 3 shows the detailed process of iris segmentation using the conditional dilation technique with gradient magnitude calculation.…”

Section: Iris Segmentation Using Gradient Magnitude and Fourier Descrmentioning

confidence: 99%

“…In a previous study, Sentanoe [3] investigated an iris segmentation module and successfully implemented a conditional dilation technique by using a gradient magnitude calculation. The results of this study were quite promising.…”

Section: Introductionmentioning

confidence: 99%

“…Thick eyelashes causing eyelashes to be detected as pupil region. 3. Noise in the pupil area causing failure in finding an accurate pupil and iris area.…”

Section: Introductionmentioning

confidence: 99%

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Iris Segmentation using Gradient Magnitude and Fourier Descriptor for Multimodal Biometric Authentication System

2016

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Perfectly segmenting the area of the iris is one of the most important steps in iris recognition. There are several problematic areas that affect the accuracy of the iris segmentation step, such as eyelids, eyelashes, glasses, pupil (due to less accurate iris segmentation), motion blur, and lighting and specular reflections. To solve these problems, gradient magnitude and Fourier descriptor are employed to do iris segmentation in the proposed Multimodal Biometric Authentication System (MBAS). This approach showed quite promising results, i.e. an accuracy rate of 97%. The result of the iris recognition system was combined with the result of an open-source fingerprint recognition system to develop a multimodal biometrics authentication system. The results of the fusion between iris and fingerprint authentication were 99% accurate. Data from Multimedia Malaysia University (MMUI) and our own prepared database, the SGU-MB-1 dataset, were used to test the accuracy of the proposed system.

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Section: Proposed Methodsmentioning

confidence: 83%

Section: Related Workmentioning

confidence: 99%

Section: Iris Segmentation Using Gradient Magnitude and Fourier Descrmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Thick eyelashes causing eyelashes to be detected as pupil region. 3. Noise in the pupil area causing failure in finding an accurate pupil and iris area.…”

Section: Introductionmentioning

confidence: 99%

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