Name
Abstract | ||
|---|---|---|
In this paper a novel and robust method for automatic iris segmentation based on local areas is described. Such method is composed of three main parts. (a) Find the local rectangle region which has the minimum intensity mean and extend it to locate pupil. (b) Select two small local sector areas including the outer boundaries of iris to locate outer iris. (c) Translate the iris from polar coordinates into Cartesian coordinates and normalize it to fixed size to compensate the stretching of the iris texture as the pupil changes in size and remove the nonconcentricity of the iris and the pupil. The method was implemented using CASIA Iris image databases. The experimental results show that the proposed method has an encouraging result with an overall accuracy of 98.42%. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICPR.2006.300 | ICPR (4) |
Keywords | Field | DocType |
automatic iris segmentation,small local sector area,local area,robust method,pupil change,local areas,outer iris,local rectangle region,fixed size,iris texture,polar coordinates,geometry,image segmentation,cartesian coordinates,image texture,polar coordinate | Computer vision,Normalization (statistics),Pattern recognition,Image texture,Segmentation,Computer science,Rectangle,Pupil,Image segmentation,Polar coordinate system,Artificial intelligence,Cartesian coordinate system | Conference |
ISSN | ISBN | Citations |
1051-4651 | 0-7695-2521-0 | 9 |
PageRank | References | Authors |
0.74 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guangzhu Xu | 1 | 25 | 4.41 |
| Zaifeng Zhang | 2 | 16 | 1.74 |
| Yide Ma | 3 | 459 | 34.74 |