Iris image segmentation based on approximate methods with subsequent refinements

A system of methods for the detection and segmentation of iris in frontal eye images is presented. Input data are images used in modern iris recognition systems. Coordinates of outer and inner iris borders and the mask of the visible iris region or a decision that the image does not contain the iris...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of computer & systems sciences international Jg. 53; H. 2; S. 224 - 238
Hauptverfasser: Gankin, K. A., Gneushev, A. N., Matveev, I. A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Moscow Pleiades Publishing 01.03.2014
Springer Nature B.V
Schlagworte:
Acceptability
Algorithms
Analysis
Approximation
Borders
Control
Engineering
Eyes & eyesight
Image detection
Image segmentation
Mechatronics
Methods
Pattern Recognition and Image Processing
Pattern recognition systems
Robotics
Segmentation
Studies
Equal Error Rate
Iris Recognition
System Science International
Pupil Center
Brightness Gradient
ISSN:1064-2307, 1555-6530
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:A system of methods for the detection and segmentation of iris in frontal eye images is presented. Input data are images used in modern iris recognition systems. Coordinates of outer and inner iris borders and the mask of the visible iris region or a decision that the image does not contain the iris of acceptable quality are obtained at the output. The system starts processing with an approximate detection of the eye center followed by an approximate detection of the outer and inner iris borders. If one of these borders is not detected, a further attempt is made to locate it using a different algorithm. Ultimately, the precise borders of the iris are determined at the last steps using specifically designed methods. The system is tested on public iris image databases as well as using the international IREX NIST test.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:1064-2307
1555-6530
DOI:10.1134/S1064230714020099