OCULAR RECOGNITION FOR BLINKING EYES

Abstract

Ocular recognition is expected to provide a higher flexibility in handling practical applications as oppose to the iris recognition, which only works for the ideal open-eye case. However, the accuracy of the recent efforts is still far from satisfactory at uncontrollable conditions, such as eye blinking which implies any poses of eyes. To address these issues, the skin texture, eyelids, and additional geometrical features are employed. In addition, to achieve higher accuracy, sequential forward floating selection (SFFS) is utilized to select the best feature combinations. Finally, the non-linear SVM is applied for identification purpose. Experimental results demonstrate that the proposed algorithm achieves the best accuracy for both open eye and blinking eye scenarios. As a result, it offers greater flexibility for the prospective subjects during recognition as well as higher reliability for security.

Existing System

Scale-invariant feature transform (SIFT) and local binary pattern (LBPLBP)

Proposed System

In the proposed algorithm, the landmark points of eyes are firstly detected. To suppress the influences of skin colors and lighting conditions, the geometric feature, which particularly describes the contours of eyes, are considered. The weighted texture texture-based LBP (WT WT-LBP) is proposed to extract the texture property of the selected regions. In addition, the probabilities of single- and double double-fold eyelids are also derived for description. To further enhance the performance, the combination of various features with the sequential forward floating selection (SFFS) is further utilized. Finally, the non -linear support vector machine (SVM) is applied for classification purpose. Experiment results suggest that the proposed ocular recognition method achieves excellent performance on three different face databases, which in turn suggests that the proposed method is an attractive candidate for practical biometrics application applications.

Architecture

BLOCK DIAGRAM