Metode Moment Invariant Geometrik untuk Menganalisis Jenis Daging Babi dan Daging Sapi - Nurhayati, Oky Dwi; hastuti, Isti Pudji (Universitas Diponegoro, 2018)
Beef needs have increased every year. So as the need for expensive beef even at certain times tends to rise. This is used by cheat seller to mix beef with pork because pork is relatively cheaper. This is very detrimental to consumers. Visually, many peoples (consumers) couldn’t distinguish these two types of meat. Hence, we conduct research to distinguish both types of meat. One way to overcome these problems is the use of complete image processing techniques. The aim of this research was establised an application prototype to distinguish beef and pork with image processing techniques. Image processing method is used to distinguish the types of meat done by pre-processing, segmentation, feature extraction with geometrical moment invariant and K-NN classification. Geometric moment invariant method proposed to analyze beef and pork is done by extracting unique values from each images. This method can be used as a description of the form based on the moment theory. The results showed that the image processing method and K-NN classification with a value of k = 3 used in the research could significantly used to analyze the type of meat namely beef and pork. The other difference can be shown from the phi moment invariant value, especially the value of phi (1) and phi (2)