Wyniki wyszukiwania - BazTech

1

An effective iris segmentation scheme for noisy images

Jan Farmanullah, Min-Allah Nasro

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 3

1064--1080

EN

Iris segmentation plays a critical role in the iris biometric systems. It has two modules: iris localization and noise detection. The first module demarcates the actual iris' inner and outer boundaries in input eyeimages. The second module detects and removes noise in the valid iris part. Researchers devised numerous iris segmentation and/or localization schemes, which are based on the histogram and thresholding, circular Hough transform (CHT), Integro-differential operator (IDO), active contour models, graph-cuts, or deep learning. It is observed that most contemporary schemes perform poorly when confronted with images containing noisy factors such as the eyebrows, eyelashes, contact lenses, non-uniform illumination, light reflections, defocus and/or eyeglasses. The performance of CHT and IDO against noise is found robust, but these operators are computationally expensive. On the other hand, the histogram and thresholding-based schemes are considered fast, but these are less robust against noise. Besides, most contemporary schemes mark iris contours with a circle approximation and offer no noise removal strategy. To address these issues, this study offers an effective iris segmentation algorithm. First, it applies an optimized coarse-to-fine scheme based on an adaptive threshold to mark iris inner boundary. Next, it detects and marks eyelashes adaptively. After that, it marks iris outer boundary via an optimized coarse- to-fine scheme. Then, it regularizes the non-circular iris' contours using the Fourier series. Finally, eyelids and reflections are marked in the iris polar form. The proposed scheme shows better results on the CASIA-Iris-Interval V3.0, IITD V1.0, and MMU V1.0 iris databases.

2

Segmentacja obrazu oka na potrzeby systemu identyfikacji osób na podstawie wzoru tęczówki

Sankowski W., Grabowski K., Zubert M., Napieralska M.

Elektronika : konstrukcje, technologie, zastosowania

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2007

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Vol. 48, nr 10

13-17

PL

Celem prezentowanych w artykule badań było opracowanie i zweryfikowanie algorytmu segmentacji obrazu oka, przeznaczonego do systemu identyfikacji osób przy wykorzystaniu wzoru tęczówki. Pierwsza część artykułu stanowi wprowadzenie do biometrii oraz przegląd znanych w literaturze metod segmentacji obrazu oka. Zaproponowany algorytm, przedstawiony w drugiej części artykułu, został zaimplementowany w języku C++, a następnie zweryfikowany na dostępnych bazach danych pozwolił uzyskać wysoki poziom skuteczności segmentacji.

EN

The aim of the presented researches was to perform and verify algorithm for eye image segmentation that would be applied in iris recognition system. The first part of the paper contains introduction to biometry and literature survey. Proposed algorithm, described in the second part of this paper, has been implemented in the C++ programming language and verified on available databases, for which the authors have achieved high level of segmentation effectiveness.

3

Iris Finder - program for reliable iris localisation in images taken under visible light

Sankowski W., Grabowski K., Zubert M., Napieralska M.

Journal of Medical Informatics & Technologies

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2006

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Vol. 10

125--132

EN

In this paper the Iris Finder program is presented for the first time. It is software for reliable iris localisation in images taken under visible light. The program is intended for researches on a system for automatic persons identification based on iris pattern. Performance of the software was verified on two databases. For the first database the program correctly localises iris for all 141 images. For the second database the iris was incorrectly localised only for 4 images from the entire database containing 1205 units.