4. LITERATURE REVIEW Past research has been proven that methods such as color classifier [7] can differentiate by obtaining RGB value from acquired image and converted to HIS value. While other researcher doing rice quality grading by checking the internal broken of rice kernel [10]. Nowadays, there are a lots of technologies can be applied in rice grading and classification around the world. Most advanced technologies has been used is by using camera or machine vision technologies systems. Machine vision means a vision system which interfacing special hardware with camera and software to process all calculation or algorithm needed to obtain a final result [11]. One method to do rice grading is using image processing .Image of rice is needed before proceed to obtain final result. The image can be in static image or in video motion which can deal with real time classification. Every rice should be in the range in order to be good grade. If is have to differ from other that really shows it’s not normal and can reduce the grade. First of all, sample of several good grade, medium grade, not good and worst grade rice is taken as a sample for the template matching, then after try several trial, the machine is learn to know how to classified between good, medium, not good and worst we named it as grade A, B, C, D and E respectively. Then try with another test image several times to make sure the process is work properly