Comparison Analysis of Montford Similarity and Mean Manhattan Distance Methods in Recognizing Human Nose Pattern

Abstract

When you meet someone you just met, the face is the first part that becomes a marker in the brain recording. The face consists of eyes, nose, and mouth which must have different shapes from one human to another, one of the most prominent parts of the face is the nose, the nose is also one of the important icons for women or men in supporting their appearance, this is proven With the increasing number of cases of plastic surgery being carried out in order to get the best nose results, to perform the rhinoplasty, it is necessary to know in advance the type of nose to be operated on. There are several nose patterns on the human face, namely, sharp, pug, small and large. The purpose of this study is to build an application to recognize the human nose pattern on the front view by comparing two algorithms, namely Montford Similarity and Mean Manhattan Distance to determine the performance of each of these algorithms in processing data on the image of the human nose so that the application can be used. for the development of nasal pattern stages with other positions. The research method consists of several stages, namely the image input stage, image resizing, grayscale and the last stage is calculating the energy value of Montford Similarity and Mean Manhattan.