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Full metadata record
DC Field | Value | Language |
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dc.contributor.author | David, Ibitayo Lanlege | - |
dc.contributor.author | Kayode, Rufu Adeboye | - |
dc.contributor.author | Yusuph, Amuda Yahaya | - |
dc.contributor.author | Audu, Isah | - |
dc.date.accessioned | 2021-08-18T12:47:28Z | - |
dc.date.available | 2021-08-18T12:47:28Z | - |
dc.date.issued | 2015 | - |
dc.identifier.issn | 1583-0233 | - |
dc.identifier.uri | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/13629 | - |
dc.description.abstract | This manuscript presents a method for segmentation of iris images based on a deformable contour (active contour) paradigm. The deformable contour is a novel approach in image segmentation. A type of active contour is the Snake. Snake is a parametric curve defined within the domain of the image. Snake properties are specified through a function called energy functional. This means they consist of packets of energy which expressed as partial Differential Equations. The partial Differential Equation is the controlling engine of the active contour since this project, the Finite Element Method (Standard Galerkin Method) implementation for deformable model is presented. | en_US |
dc.publisher | Leonardo Journal of Sciences | en_US |
dc.relation.ispartofseries | Issue 26;1-16 | - |
dc.subject | Multiscale Active Contour Model | en_US |
dc.subject | Iris Segmentation | en_US |
dc.subject | Finite Element Method (Standard Galerkin Method) | en_US |
dc.subject | Partial Differential Equation | en_US |
dc.title | The iris biometric feature segmentation using finite element method | en_US |
dc.type | Article | en_US |
Appears in Collections: | Statistics |
Files in This Item:
File | Description | Size | Format | |
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Iris Biometric Feature.pdf | 195.62 kB | Adobe PDF | View/Open |
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