An Algorithm to Extract the Costume’s Size by Fuzzy Logic

Abstract

This study presents the algorithm to extract the size of the ready-to-wear clothing, which is men's T-shirts with f. house branding. The table has four sizes, and the size labels are signed by S, M, L, and XL. Authors use fuzzy logic to establish the algorithm model. In this model, the input variables have three inputs, which are the body height, weight, and bust girth measurements. In the output variables are the results of size coding. From this size chart table, the authors choose the primary dimensions to be the input variables of the algorithm. The first dimension is a vertical dimension, and the other two dimensions are horizontal dimensions. The vertical dimension is height. Two horizontal dimensions are weight and bust girth. The sizes in the table are encoded to be used for the algorithm results, and the output is the encoded sequence number, which is also the size to be searched. After running this simulation program, measurements of three primary dimensions in size are tested on customers using two methods for two objects. An algorithm for extracting the size of ready-to-wear clothes by the fuzzy logic method reduces the time it takes to choose the size that fits body measurements. In addition, this research direction is consistent with the trend of digital development.