Name
Abstract | ||
|---|---|---|
This paper presents an efficient iris segmentation algorithm. This paper uses an improved circular Hough transform to detect inner boundary and the circular integro-differential operator to detect the outer boundary of iris from a given eye image. Search space of the standard circular Hough transform is reduced from three dimensions to only one dimension, which is the radius. Local gradient information is used to improve time and efficiency of Hough transform. This algorithm has been tested on the publicly available CASIA 3.0 Interval database consisting of 2639 images of 249 subjects and CASIA 4.0 Lamp database consisting of 16,212 images of 411 subjects. It also provides error categorization for wrong segmentation, as well as a study on parametric influences on error. Parameterized error analysis helps to set parameters intelligently boosting up the segmentation accuracy as high as 99.8% on the Interval database and 99.7% on the Lamp database. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-31837-5_59 | Communications in Computer and Information Science |
Keywords | Field | DocType |
Hough Transform,Integro-differential operator,Iris Segmentation,Occlusion,Illumination | Categorization,Parameterized complexity,Scale-space segmentation,Pattern recognition,Segmentation,Computer science,Hough transform,Parametric statistics,Boosting (machine learning),Operator (computer programming),Artificial intelligence | Conference |
Volume | ISSN | Citations |
304 | 1865-0929 | 15 |
PageRank | References | Authors |
0.88 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amit Bendale | 1 | 21 | 2.02 |
| Aditya Nigam | 2 | 154 | 28.82 |
| Surya Prakash | 3 | 159 | 19.79 |
| Phalguni Gupta | 4 | 805 | 82.58 |