Pupil Segmentation of Abnormal Eye using Image Enhancement in Spatial Domain

Abstract

Segmentation is one of the important elements in image processing. There are various types of algorithms that have been developed by researchers, for segmenting the interesting area for classification and identification purposes. This paper, presents the pupil segmentation using logarithmic transformation (LT) and power law transformation (PLT). It is obviously seen in most of the work on pupil segmentation where assumption is made that the pupil has a homogeneous circular. However, there are cases where the shape of pupil is inhomogeneous, for instance, in synechia case. Therefore, the use of circumference equation such as circular Hough transforms (CHT) and Daugman's Integra-differential operator (DIDO) for section the non-uniform pupil will produce inaccurate segmentation. We propose a new method for pupil segmentation using the combination of LT and PLT algorithm in order to enhance the pupil segmentation. The morphological operators and black white (BW) removal are used the segmentation of pupil. The proposed system uses CASIA V1, CASIAV3 Interval and MMU1 iris database. The results show his method gives accurate segmentation compared to CHT or DIDO technique.