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 ...

A new iris recognition method based on a robust iris segmentation approach is presented in this paper for improving iris recognition performance. The robust iris segmentation approach applies power-law transformations for more accurate detection of the pupil region, which significantly reduces the candidate limbic boundary search space for increasing detection accuracy and efficiency. The limbi...

Since iris muscles control the size of the pupil, iris pattern shown in a captured iris image deforms significantly during pupil dilation/constriction. Daugman-based approaches assume the iris deformation is linear when mapping the iris to the polar rectangular format. However, iris deformation is not linear and in fact differs from person to person. To cope with the non-linear iris deformation...

Iris segmentation is one of the most important steps in an iris recognition system. Its accuracy can directly affect the recognition accuracy. For non-cooperative users, the obtained images often do not have good quality. Under such conditions, the iris may be deformed, out-of-focus, or motion blurred. Sometimes, images do not have a valid iris. It is very challenging to segment the iris effici...

Existing iris recognition systems are heavily dependent on specific conditions, such as the distance of image acquisition and the stop-and-stare environment, which require significant user cooperation. In environments where user cooperation is not guaranteed, prevailing segmentation schemes of the iris region are confronted with many problems, such as heavy occlusion of eyelashes, invalid off-a...

The biometric person authentication technique based on the pattern of the human iris is well suited to be applied to any access control system requiring a high level of security. Iris recognition is a proven, accurate means to identify people. Iris recognition system includes the preprocessing system, segmentation, features extraction and recognition. Especially we focus on image segmentation a...

A novel iris segmentation approach for noisy iris is proposed in this paper. The proposed approach comprises of specular reflection removal, pupil localization, iris localization and eyelid localization. Reflection map computation is devised to get the reflection ROI of eye image using adaptive threshold technique. Bilinear interpolation is used to fill these reflection points in the eye image....

Iris patterns have been proven to be unique for each individual making them useful in human identification. Segmentation and feature extraction are crucial steps in matching one iris image with another. In this paper, iris segmentation is performed using Canny edge detection and the circular Hough transform. To overcome the pupil-iris center offset as well as iris stretching due to pupil dilati...

A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. Iris recognition systems capture an image of an individual's eye, the iris in the image is then segmented and normalized for feature extraction proc...

Iris segmentation is almost the most challenging part in iris recognition. Several robust algorithms in the recognition part have been developed in literature yet. In this paper, we focus on an efficient approach for iris segmentation. The main purposes are to improve accuracy and to reduce computational time of iris localization. Briefly, this approach tries to explore regions of interests (RO...