UBIRIS: A Noisy Iris Image Database

By Hugo Proença, Luís A. Alexandre. International Conference on Image Analysis and Processing, 2005

608 citations recorded by the source corpus.

Subfields: Genetics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/be9124db35e5f451f508e095fdc25727c067a9ef

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. Zhaofeng He
2. Zhenan Sun
3. Tien-Ping Tan
4. Richa Singh
5. Mayank Vatsa
6. Afzel Noore

In Signal Processing

1. Zhenan Sun
2. Zhaofeng He
3. Richa Singh
4. Mayank Vatsa
5. Tien-Ping Tan
6. Afzel Noore
7. Sébastien Marcel
8. Almas Abbasi

Citations in the corpus

• Efficient and robust segmentation of noisy iris images for non-cooperative iris recognition (2010, methodology): “In this section, experiments are carried out on the UBIRIS iris image databases [4,18] to evaluate the effectiveness of the proposed methods.”
• Toward Accurate and Fast Iris Segmentation for Iris Biometrics (2009, neutral): “It includes 1,877 images captured from 241 subjects in two distinct sessions [37].”
• Improving Iris Recognition Performance Using Segmentation, Quality Enhancement, Match Score Fusion, and Indexing (2008, methodology): “1 from the UBIRIS database [26], [27] shows images with some of the above mentioned problems.”