Comparison of Histogram Based Image Enhancement Methods on Iris Images

Abstract

Abstract 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.