Abstract—Iris recognition is one of the most prevalent methods for personal identification in the modern day. Low quality iris images that are blurry, of low resolution, and poor illumination poses a big challenge for iris recognition as the iris recognition efficiency is entirely dependent on whether the image supplied is of good quality. Therefore, several enhancement techniques have been proposed and used for image processing to increase the quality of iris images. Although there is no best approach for all types of image enhancement, histogram equalization (HE) is a commonly used approach as it is a simple yet effective method. In this paper, several enhancement techniques based on histogram equalization approaches, such as histogram equalization (HE), brightness preserving bi-histogram equalization (BBHE), dynamic histogram equalization (DHE), adaptive histogram equalization (AHE), contrast limited adaptive histogram equalization (CLAHE), dualistic sub-image histogram equalization (DSIHE), and multi-scale adaptive histogram equalization (MAHE), have been explored. A comparison is conducted based on the image quality of all image enhancement techniques proposed in this paper.

Index Terms—biometric approach, histogram equalization, Iris recognition, Iris enhancement

Cite: Sanpachai H. and Settapong Malisuwan, "A Study of Image Enhancement for Iris Recognition," Journal of Industrial and Intelligent Information, Vol. 3, No. 1, pp. 61-64, March 2015. doi: 10.12720/jiii.3.1.61-64