Introduction

An individual’s biometrics include fingerprints, palm-prints, retinal, iris and speech patterns. Even the way people move and sign their name has been shown to be uniquely associated with that individual. This work focuses on the recognition of an individual’s iris patterns.

The results reported in the literature are often presented in such a manner that direct comparison between methods is difficult. There is also minimal code resource and no tool available to help simplify the process of developing iris recognition algorithms, so individual developers are required to write the necessary software almost every time. Finally, segmentation performance is currently only measurable using manual evaluation, which is time consuming and prone to human error.

The generic platform is a completely novel MATLAB based software platform for the purposes of developing, testing and evaluating iris recognition algorithms. The platform is designed to simplify the process of developing and testing iris recognition algorithms. Existing open-source algorithms have been integrated into the generic platform and evaluated using the results it produces.

The research that resulted in the generic platform also proposed three iris recognition segmentation algorithms and one normalisation algorithm. Three of the algorithms increased true match recognition performance by between two and 45 percentage points when compared to the available open-source algorithms and methods found in the literature. A matching algorithm was developed that significantly speeds up the process of analysing the results of encoding within the MATLAB environment. Lastly, the generic platform also implements a method of automatically evaluating the performance of segmentation algorithms, so minimising the need for manual evaluation.

[Getting Started]

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Project Members:

• ChrisP (admin)