Texture Detection for Segmentation of Iris Images ASHEER KASAR BACHOO University of Kwa-Zulu Natal, South Africa and JULES-RAYMOND TAPAMO University of Kwa-Zulu Natal, South Africa The idea of using the distinct spatial distribution of patterns in the human iris for person authentication is now a widely developing technology. Current systems rely on a set of basic assumptions in order to improve the accuracy and running time of the recognition process. The advent of a robust system implies a viable solution to a number of general problems. This paper focuses on a common yet difficult problem - the segmentation of eyelashes from iris texture. Tests give promising results when using grey level co-occurrence matrix (GLCM) approach. Categories and Subject Descriptors: I.4.6. [Image Processing and Computer Vision]: Segmentation - region growing and partition; I.5.3. [Pattern Recognition]: Clustering - algorithms, similarity measures General Terms: texture, classification, experimentation Additional Key Words and Phrases: iris, localization, GLCM, K-Means 1. INTRODUCTION The iris begins its formation in the 3 rd month of gestation [Adler 1965]. By the 8 th month, its distinctive pattern is complete. However, pigmentation and even pupil size increase as far up as adolescence [Kronfeld 1968]. The iris has a multilayered texture. This combination of layers and colour provide a highly distinctive pattern. An assortment of texture variations are possible. They include: —Contractile lines related to the state of the pupil —Crypts - irregular atrophy of the border layer. —Naevi - small elevations of the border layer. —Freckles - collections of chromatophores. —Colour variation - an increase in pigmentation yields darker coloured irides. Of the utmost importance in a biometric identification system is the stability and uniqueness of the object being analysed. Ophthalmologists [Flom and Safir 1987] and anatomists [Davson 1990], during the course of clinical observations, have noted that the irises of individuals are highly distinctive. This extends to the left and right eye of the same person. Repeated observations over a period of time have highlighted little variation in the patterns. Developmental biology has also provided evidence of the particular characteristics of the iris [Kronfeld 1968]. Although the general structure of the iris is genetically determined, the uniqueness of its minutiae is highly dependent on circumstances. As a result, replication is almost impossible. It has also been noted that, following adolescence, the iris remains stable and varies little for the remainder of the person’s life. Development is continuous during the early and adolescent years (pigmentation continues as well as an increase in pupil size) [Davson 1990; Kronfeld 1968]. Figure 1 shows an iris and the variety of its texture patterns. In 1936, Frank Burch, an ophthalmologist, proposed the idea of using iris patterns for personal identification. However, this was only documented by James Doggarts in 1949. The idea of iris identification for automated recognition was finally patented by Aran Safir and Leonard Flom in 1987. Although they had patented the idea, the two ophthalmologists were unsure as to a practical implementation for the system. They commissioned John Daugman to develop the fundamental algorithms in 1989. These algorithms were patented by Daugman in 1994 Asheer Kasar Bachoo, School of Computer Science, University of Kwa-Zulu Natal, Durban, 4041, e-mail - 200266744@ukzn.ac.za Jules-Raymond Tapamo, School of Computer Science, University of Kwa-Zulu Natal, Durban, 4041, e-mail - tapamoj@ukzn.ac.za Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage, that the copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than SAICSIT or the ACM must be honoured. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. c  2005 SAICSIT Proceedings of SAICSIT 2005, Pages 111–118