Pork and Beef Features Extractions

Increased demand for meat in the market causes various problems, including misuse of sales by mixing beef with pork. The similarity between meat as making a layman is difficult to distinguish between meat. Ignorance makes consumers can not distinguish the type of meat that makes consumers just the origin of buying meat. Therefore, the introduction of meat is important to ensure that meat is certain. Color and texture is one of the characteristics of every meat. In this study we used the introduction of meat using images using histogram-based texture extraction and HSI color feature extraction. The result of feature extraction obtained then processed by using Neural Network, SVM, and KNN method to be grouped into two classes of meat, namely pork and beef. The determination of the success of this classification process is evaluated by using a confusion matrix which yields an accuracy of 93.75% using k-fold 20 with Neural Network method for the classification.