A Novel Iris Clustering Approach Using LAB Color Features

Radu, Petru and Sirlantzis, Konstantinos and Howells, Gareth and Hoque, Sanaul and Deravi, Farzin (2013) A Novel Iris Clustering Approach Using LAB Color Features. In: 4th IEEE International Symposium on Electrical And Electronics Engineering (ISEEE 2013), 11-13 October 2013, Galati, Romania. (doi:https://doi.org/10.1109/ISEEE.2013.6674362) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Official URL
http://dx.doi.org/10.1109/ISEEE.2013.6674362

Abstract

Interesting results of color clustering for the iris images in the UBIRISv1 database are presented. The iris colors are characterized by feature vectors with 80 components corresponding to histogram bins computed in the CIELAB color space. The feature extraction is applied to the first session eye images after undergoing an iris segmentation process. An agglomerative hierarchical algorithm is used to organize 1.205 segmented iris images in 8 clusters based on their color content.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: CIELAB color space; LAB color features; UBIRISv1 database; agglomerative hierarchical algorithm; color clustering; feature extraction; feature vectors; first session eye images; histogram bins; iris clustering approach; iris images; iris segmentation process;
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image Analysis, Image Processing
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Konstantinos Sirlantzis
Date Deposited: 14 Dec 2015 01:13 UTC
Last Modified: 17 Dec 2015 09:31 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/53300 (The current URI for this page, for reference purposes)
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