Iris segmentation using pupil location, linearization, and limbus boundary reconstruction in ambient intelligent environments

Abstract

Advances in sensors and technology, on one side, and recognition techniques, on the other side, make the iris a top candidate for biometric use. Iris detection and segmentation, however, are still lacking. We propose here a novel iris segmentation technique using pupil location, linearization, and limbus boundary reconstruction, and show its feasibility and comparative advantages against existing methods

Iris recognition system based on video for unconstrained environments

“…Regarding the performance of segmentation quality evaluation stage, proposed scheme achieves a correctly evaluation rate equal to 99%, that is, 98.85% of correctly segmented image and 99.33% of wrongly segmented image were correctly classified. This performance appears to be good enough for most practical applications; however, it may be improved incorporating the segmentation quality evaluation criteria proposed by De Marsico et al (2011). Thus, instead of using a SVM with 3 inputs and 2 outputs, a SVM with 5 or more inputs and 2 outputs may be used.…”

“…Thus, the detection and elimination of the bad-quality eye frames and non-properly segmented iris frames could help to improve the recognition accuracy and then to reduce the processing time. De Marsico et al (2010Marsico et al ( , 2011 proposed an efficient iris segmentation algorithm using pupil localization, as well as pupil-iris limbic boundaries reconstruction. They also introduce some criteria that can be used to determine the quality of segmented iris.…”