Iridology, which is an alternative diagnosis that links iris patterns, colour, tissue weakness, damage and other characteristics, which can obtain evidence about the patient’s systemic health. Iridology can be integrated with the best technology such as computer vision for accurate identification of abnormalities in various organs of the human body. By extracting information from iris image data. Image quality improvement is needed because often the images tested have poor quality, for example images experiencing lighting, noise (noise), the image is too dark or bright, the image is not sharp, and blurred. In this research, the iris image quality was improved by the method of HE, AHE and CLAHE. The results of the improvement of 40 iris images obtained an average value of MSE and RSME, the smallest of the three methods is the CLAHE method, so that the CLAHE method is best used for iris image improvement. Overall, based on the PSNR values, the three methods are good for enhancing image contrast because they have an average PSNR of more than 30dB.

Authors: R K Hapsari^1,2, M I Utoyo³, R Rulaningtyas⁴ and H Suprajitno³

1Doktoral Student at Faculty of Sciences and Technology, Airlangga University, Surabaya,
Indonesia.
2Department of Informatics, Faculty of Electrical and Information Technology, Adhi Tama
Institute of Technology Surabaya, East Java, Indonesia
3Department of Mathematics, Faculty of Sciences and Technology, Airlangga University,
Surabaya, Indonesia
4Department of Physics, Faculty of Sciences and Technology, Airlangga University, Surabaya,
Indonesia

Download full abstract: Hapsari_2020_J._Phys. _Conf._Ser._1569_022002