Comparison Of Accuracy Level Of Krisch And Prewitt Methods For Measurement Of Human Body Weight Using Digital Images

Abstract

Current image processing provides an opportunity for humans to develop systems capable of identifying digital images. Edge detection is a process to produce the edges of an image object. The problem of this research is how to compare the level of accuracy of the Krisch and Prewitt method for measuring human body weight with digital images. The aim of this research is to compare the level of accuracy between the Krisch and Prewitt methods in measuring human body weight using digital images. This research uses an experimental method by taking images of the human body, cropping, resizing, and converting them into grayscale images. Next, edge detection was carried out using the Krisch and Prewitt method. Edge detection results are used to measure human body weight by calculating the pixel distance between certain points on the edge of the object in the image. The results of this study show that the Krisch and Prewitt methods have different levels of accuracy in measuring human body weight. Based on tests that have been carried out on 15 image data samples using the confusion matrix approach, where the accuracy level of the Prewitt method is 60% while the Krisch method is 40%. The conclusion of the research is that the Prewitt method has the best level of accuracy compared to the Krisch method