An Improved Bovine Iris Segmentation Method

A New IRIS Segmentation Method Based on Sparse Representation

Iris recognition is one of the most reliable methods for identification. In general, itconsists of image acquisition, iris segmentation, feature extraction and matching. Among them, iris segmentation has an important role on the performance of any iris recognition system. Eyes nonlinear movement, occlusion, and specular reflection are main challenges for any iris segmentation method. In thi...

A New IRIS Segmentation Method Based on Sparse Representation

Iris recognition is one of the most reliable methods for identification. In general, itconsists of image acquisition, iris segmentation, feature extraction and matching. Among them, iris segmentation has an important role on the performance of any iris recognition system. Eyes nonlinear movement, occlusion, and specular reflection are main challenges for any iris segmentation method. In thi...

A New IRIS Segmentation Method

Iris Segmentation Using Improved Hough Transform

This paper presents an efficient iris segmentation algorithm. It uses an improved circular Hough transform to detect the inner boundary and the integro-differential operator to detect the outer boundary of iris from a given eye image. Search space of the standard circular Hough transform is reduced from three dimensions (center coordinates and radius) to only one dimension, which is the radius....

Efficient Iris Identification with Improved Segmentation Techniques

In this chapter, the authors propose and implement an improved iris recognition method based on image enhancement and heuristics. They make major improvements in the iris segmentation phase. In particular, the authors implement the raised to power operation for more accurate detection of the pupil region. Additionally, with their technique they are able to considerably reduce the candidate limb...