Robust security using code level approach for iris recognition

Robust security using code level approach for iris recognition
Author(s):
NIGILA S, Dr.G.Gandhimathi
Keywords:
Homogenous iris, score-level solutions
Abstract
Matching heterogeneous iris images in less con-strained applications of iris biometrics is becoming a challenging task. The existing solutions try to reduce the difference between heterogeneous iris images in pixel intensities or filtered features. In contrast, this paper proposes a code-level approach in het-erogenous iris recognition. The non-linear relationship between binary feature codes of heterogeneous iris images is modeled by an adapted Markov network. This model transforms the number of iris templates in the probe into a homogenous iris template corresponding to the gallery sample. In addition, a weight map on the reliability of binary codes in the iris template can be derived from the model. The learnt iris template and weight map are jointly used in building a robust iris matcher against the variations of imaging sensors, capturing distance and subject conditions. Extensive experimental results of matching cross-sensor, high-resolution vs low-resolution and, clear vs blurred iris images demonstrate the code-level approach can achieve the highest accuracy in compared to the existing pixel-level, feature-level and score-level solutions
Article Details
Unique Paper ID: 146582 Publication Volume & Issue: Volume 4, Issue 12 Page(s): 942 - 948
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org