| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 526050 | Computer Vision and Image Understanding | 2011 | 6 Pages |
In this paper, we present a new method for iris recognition based on elastic graph matching and Gabor wavelets. We have used the circular Hough transform to determine the iris boundaries. Individual segmented irises are represented as labeled graphs. Nodes are labeled with jets; edges are labeled with distance vectors. A similarity function is defined to compare two graphs, taking into account the similarities of individual jets and the relative distortion of the graphs. For matching and recognition, only jets referring to corresponding points are compared. Recognition results are given for galleries of irises from CASIA version 1 and UBIRIS databases. The numerical results show that, the elastic graph matching is a effective technique for iris matching process. We also compare our results with previous results and find out that, the elastic graph matching is an effective matching performance.
► We have presented the Elastic Graph Matching (EGM) as a new approach for iris recognition. ► We have used the circular Hough transform to determine the iris boundaries. ► Individual segmented irises are represented as labeled graph with jets; edges are labeled with distance vectors. ► A similarity function is defined to compare two graphs. ► The numerical results show that, elastic graph matching is an effective technique for iris recognition.
