Reliable and fast eye finding in close-up images

Abstract

This paper describes a method f o r quickly and robustly localizing the iris and pupil boundaries of a human eye in close-up images. Such an algorithm can be critical for iris identifcotion, or for applications that must detemzine the subject's gaze direction, e.g., human-computer interaction or driver attentiveness determination. A multi-resolution coarse-toTfne search appmach is used, seeking to maximize gradient strengths and uniformities measured across rays radiating from a candidate iris or ptipil's cenrral poinr. An empirical evaluation of 670 eye images. both with and without glasses, resulted in a 98% localization accuracy. The algorithm has also shown robustness tu weak illuminarion and mosf specular repertions (e.g., at exewear and cornea), simplij+)ing system component requirements. Rapid execution is achieved on a 750 M H z desktop processor

Real Time Iris Image Segmentation for Non Co-Operative Environment

“…After some minor differences this operator was again proposed by Nishino & Nayar in 2004 [6]. Camus & Wildes [5] & Martin Roche et al [18] also proposed an integro differential operator which search over an N 3 space. This method maximize the equation that identify the iris border.…”

Performance Evaluation of Proposed Segmentation Framework with Existing Techniques for Noisy Iris Images

“…In this technique, Daugman assumes both pupil and iris with circular form and applies the following operator Camus and Wildes proposed a technique for localizing the iris and pupil boundaries by using multi-resolution approach of an eye in a close-up image [4]. This technique used both the pupil and iris boundaries as a component goodness-of-fit metric for boundary parameters in a polar coordinate system.…”

Automated Detection of Cholesterol Presence using Iris Recognition Algorithm

“…The segmentation algorithm is based on the Circular Hough transform is employed [10]. Initially, an edge map is created by calculating the first derivatives of the intensity values of an eye image and then set the threshold value based on the result.…”