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PROJECT TITLE :

Confidence Measure Using Composite Features for Eye Detection in a Face Recognition System

ABSTRACT:

To evaluate the eye detection findings, we offer a new confidence measure and integrate two separate eye detectors. The distances between the test sample and the positive samples, which are determined in the composite feature space, are used to determine the confidence in the results of eye detection.

We create a hybrid detector by integrating two separate detectors that are complementary to each other using the proposed confidence measure. When compared to employing an individual eye detector, the experimental results reveal that the suggested detector gives more accurate eye detection results and, as a result, improved face recognition rates.


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