Personal identification using a delaunay triangle and optic disc retinal vascular pattern
| dc.contributor.author | Kanjanasurat, Isoon | |
| dc.contributor.author | Purahong, Boonchana | |
| dc.contributor.author | Aoyama, Hisayuki | |
| dc.contributor.author | Benjangkaprasert, Chawalit | |
| dc.contributor.author | Pintavirooj, Chuchart | |
| dc.date.accessioned | 2026-08-06T10:27:15Z | |
| dc.date.available | 2026-08-06T10:27:15Z | |
| dc.date.issued | 2020-01-01 | |
| dc.description.abstract | Retinal vascular patterns are unique and individual. They provide highly secure and correct identity authentication. In this study, we exploit an image alignment approach based on a geometric invariant, which is the area spanned by feature-point triplets for personal identification. First, we located the optic disc by using a projection of the vascular structure in vascular extraction and extracted feature points that are bifurca- tions of a retinal blood vessel in the vicinity of the optic disc as the landmarks. Delaunay triangulation is then applied to the extracted feature points. The absolute invariant is then derived by taking the ratio of successive triangular area patches. The alignment is achieved by establishing correspondences between feature points after a conformal sort- ing step based on a derived set of absolute affine invariants. The affine transformation parameters can then be calculated by the corresponding vertices of the most robust neigh- bouring triangle of both inquiry and reference images. The optic disc localization results successfully located 95.95% in six widely used retinal image databases. The algorithm of vascular extraction, applied on the DRIVE database, provided an average accuracy of ap- proximately 94.1%. The best accuracy and sensitivity for neighbouring triangle matching obtained were 99.90% and 87.66%, respectively. | |
| dc.identifier.citation | International Journal of Innovative Computing Information and Control, 16(3), 879-897, 2020 | |
| dc.identifier.doi | 10.24507/ijicic.16.03.879 | |
| dc.identifier.issn | 13494198 | |
| dc.identifier.other | 2-s2.0-85086410058 | |
| dc.identifier.uri | https://dspace.kmitl.ac.th/handle/123456789/10587 | |
| dc.source | International Journal of Innovative Computing Information and Control | |
| dc.subject | Delaunay triangle | |
| dc.subject | Neighbour area ratio | |
| dc.subject | Optic disc localization | |
| dc.subject | Retinal identification | |
| dc.subject | Vessel extraction | |
| dc.title | Personal identification using a delaunay triangle and optic disc retinal vascular pattern | |
| dc.type | Article |