Iris boundaries localization is a critical model in facial feature-based recognition systems. It has a close relationship to the results’ accuracy of these applications. In this paper, we propose a new algorithm based on the angular integral projection function (AIPF) to localize eyeball (iris outer boundary ) in iris images. The proposed algorithm adopts boundary points detection and curve fit...

We present a new approach for iris recognition based on a random sampling strategy. Iris recognition is a method to identify individuals, based on the analysis of the eye iris. This technique has received a great deal of attention lately, mainly due to iris unique characterics: highly randomized appearance and impossibility to alter its features. A typical iris recognition system is composed of...

The iris texture curve features play an important role in iris recognition. Although better performance in terms of recognition effectiveness can be attained using the recognition approach based on the wavelet transform, the iris curve singularity cannot be sparsely represented by wavelet coefficients. In view of the better approximation accuracy and sparse representation ability of the Curvele...

This thesis investigates the problem of facial image analysis. Human faces contain a lot of information that is useful for many applications. For instance, the face and iris are important biometric features for security applications. Facial activity analysis such as face expression recognition is helpful for perceptual user interfaces. Developing new methods to improve recognition performance i...

Iris segmentation plays an important role in an accurate iris recognition system. In less constrained environments where iris images are captured at-a-distance and on-the-move, iris segmentation becomes much more difficult due to the effects of significant variation of eye position and size, eyebrows, eyelashes, glasses and contact lenses, and hair, together with illumination changes and varyin...

Face and iris localization is one of the most active research areas in image understanding for new applications in security and theft prevention, as well as in the development of human–machine interfaces. In the past, several methods for real-time face localization have been developed using face anthropometric templates which include face features such as eyes, eyebrows, nose and mouth. It has ...