DISTINCTION DETECTION THROUGH IRON IMAGE USING IMAGE METHOD OF NETWORK NEURAL NETWORK HEBB RULE
Iridology is a method of analyzing the iris of the eye to detect the weakness of organs through the characteristics and also
signs that appear on the iris of the eye. Iris eyes have specific advantages that can record all conditions
organs, one of which is the organ of the stomach. By utilizing biometrics and the science of iridology, then on
This Final Project built a software to detect gastric disturbances by using the method hebb rule. The mechanism of the system begins by inputting the iris image which is then changed become an image grayscale. Imagery image grayscale transformed into polar coordinates to facilitate the process taking the gastric area on the first layer of the iris. The iris image of the stomach area is then processed edge detection by using operator canny which will be used as input method hebb rule . Method hebb rule which will determine the iris of the eye that there is a stomach disorder or not by calculating the weight and net of any vector value that forms on the iris pattern of the gastric area. There are several factors that can be affect the detection process, such as noise on the input and lighting images that enter the iris area stomach. Of the 40 iris images tested there are 31 recognizable images. So the accuracy of this system is 77.50%. Based on these results, it can be concluded that the system is capable of detecting interference stomach through iris image.
Download Full Abstract: 1503561779DeteksiGangguanlambungs