Iris image quality assessment is an important part of iris recognition system because the qualities of iris images would largely influence the recognition results. In this paper, we analyze and compare several representative quality assessment methods, and then propose an effective method based on Laplacian of Gaussian operator for iris image assessment. Through computer simulations of several ...

Among many biometric identification methods iris recognition is more attractive due to the unique features of the human eye [1]. There are many proposed algorithms for iris recognition. Although all these methods are based on the properties of the iris, they are subject to some limitations. In this research we attempt to develop an algorithm for iris recognition based on Fuzzy logic incorporate...

Iris recognition is one of the most reliable methods for personal identification. However, not all the iris images obtained from the device are of high quality and suitable for recognition. In this paper, a novel approach for iris image quality assessment is proposed to select clear images in the image sequence. The proposed algorithm uses three distinctive features to distinguish three kinds o...

The goal of Iris recognition is to recognize human identity through the textural characteristics of one’s Iris muscular patterns. Iris recognition has been acknowledged as one of the most accurate biometric modalities because of its high recognition rate. Here performance comparison among various proposed techniques of Iris Recognition using the fractional coefficients of transformed Iris image...

The increasing need for information security has led to more attention being given to biometrics-based, automated personal identification. Among existing biometric approaches, the human iris is the most promising technique. In general, an iris recognition algorithm includes four basic steps: image quality assessment, image preprocessing, image feature extraction, and image matching. This paper ...

Humans have distinctive and unique traits which can be used to distinguish them from other humans, acting as a form of identification. A number of traits characterising physiological or behavioral characteristics of human can be used for biometric identification. Basic physiological characteristics are face, facial thermograms, fingerprint, iris, retina, hand geometry, odour/scent. Voice, signa...

Accurate iris segmentation is presented in this paper, which is composed of two parts, reflection detection and eyelash detection. Eyelashes are classified into two categories, separable and multiple. An edge detector is applied to detect separable eyelashes and intensity variances are used to recognize multiple eyelashes. Reflection is also divided into two types, strong and weak. A threshold ...

We propose a novel approach for iris recognition in less constrained environments that takes into account imaging noise arising from image capture outside the Depth of Field (DOF) of cameras. The proposed approach utilizes stable dark regions in iris images for recognition and does not rely on special hardware or on computationally expensive image restoration algorithms. We have employed a Gabo...

With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention over the past decade. Iris recognition, as an emerging biometric recognition approach has become a major research topic with practical applications in recent years as it promises nearly perfect recognition rates. In this paper, we present a novel, efficient appro...

In an eye image, the iris is bounded by the pupil opening on its interior and the white sclera on its exterior. The visible iris pattern is largely determined by a meshwork of muscle ligaments. The iris pattern is a promising biometric characteristic because it is thought to be unique to each eye, with a high degree of discrimination ability [1]. In fact the left and right irises from the same ...