Abstract

Iridology as a science is based on an analysis of the composition of the iris. In particular iris has specific advantages, which can record all the conditions of the organs, body construction, as well as psychological conditions. Trace records related to the intensity levels or deviations organs caused by disease recorded in a systematic and patterned on the iris of the eye and surrounding area. It can be used as a practical guideline for the diagnosis of the various diseases. Therefore, further research needs to be done about the condition of the organ diagnosis by looking at the image of the iris. In this final project, the software is able to perform feature extraction using Principal Component Analysis (PCA) and classification using Artificial Neural Networks. Eye image to be processed first separated from the image of the eye for further changes to the gray level image and the image quality improvement using adaptive histogram. The next process is to change the image of iris into rectangular form and making the Region Of Interest eye image associated with the liver, the final step is to extract the characteristics of iris image ROI using Principal Component Analysis (PCA) and customize the use of Artificial Neural Networks. From the test results, it can be concluded that the iris recognition system shows good recognition results. Of 15 tested iris image, the program can recognize the 14 images, so the introduction 96.667%.

Download abstract: 3066-5709-1-SM

Reference: https://ejournal3.undip.ac.id/index.php/transient/article/view/3066