Implementasi Sistem Klasifikasi Analisa Tekstur Dan Normalisasi Warna Terhadap Daging Sapi Dan Daging Babi Menggunakan Metode K-Means

Abstract

Textures are large areas that have certain characteristics that make these characteristics repeatable in that area naturally. What is meant by the area here is in accordance with a separate characteristic that is formed into pixels in the image. “Digital image‘processing’ (Digital’ Image’Processing) is a learning to explores a process in processing images. The processing model referred to here is the processing of color in an image. Texture analysis’is used’as a process for classifying and interpreting images. Texture analysis has 5 values ​​consisting of ASM, Contras, IDM, Entropy and Variance features. Color normalization produces three values, namely red, green, and blue. Mathematically, the image is a function of the light intensity in a two-dimensional plane. In order to be processed by a digital computer, an image must be represented numerically with discrete values. The results showed that in order to be able to distinguish the types of beef from pork so that later the meat could be distinguished using the K-Means method. So that consumers and entrepreneurs can understand and differentiate between beef and pork.

Keywords: texture, texture analysis, color normalization, k-means, difference between beef and pork