A probability approach in cans identification

Abstract

The objective of this study is to identify can waste into three types based on the images by using a probability approach of trinomial distribution in term regression. Predictor variables considered are the color intensity of red, green, and blue of the images taken at the top, down, and side pose successively. From an independence test between each of the predictor variable and can waste type noted that only the color intensity of red which the image taken at top pose that does not correspond to the can waste types. Based on the Nagelkerke value is found that the variance of the predictor variable data in identifying the can waste type is able to explain the variance of the types of 59.1 percent. The final model show that the significant predictor variables are the colors intensity of green and blue which the image taken at the top pose, the color intensity of red which the image taken at down pose, and the color intensity of red, green and blue which the image taken at side pose successively. The model can identify cans waste into three types based on the images correctly by 73.13%.