Detection of the beef quality: Using mobile-based K-mean clustering method
Oky Dwi Nurhayati, Kusworo Adi, Sri Pujiyanto · 2016
Beef quality is determined by a number of parameters; some of which include size, texture, color feature, or meat smell. Recently, determining the meat quality is done by seeing the color and shape. However this method still has some weaknesses due to, for example, the subjectivity and inconsistency in human assessment. The aim of this research is to make an application to detect the meat quality. The application built was based on mobile using Java Programming Language on the Android integrated with Android SDK, Eclipse, and OpenCV. The method of image processing used pre-processing, k-mean clustering, and the analysis was conducted statistically with mean value and deviation standard. The quality detection meanwhile was performed using the texture and meat texture matching based upon the existing data. The application made could be used to seek the significant k-values and able to detect the level of quality by providing the level of accuracy at 80%.