Artificial Neural Network for Healthy Chicken Meat Identification

Abstract

Indonesia is the country with the largest number of Muslims in the world. Every Muslim is taught to consume thoyyiban halal meat or healthy chicken because it is slaughtered in the right way and stored in a good way too. But the reality in the market of many chicken meat on the market can not meet that criteria. Identification of healthy chicken meat can be done with laboratory experiments, but that is not simple and takes time. This experiment offers a cheaper, faster approach, with very high accuracy. The experimental approach is based on color and texture analysis on 5 types of meat quality based on healthy value. Color analysis was performed using artificail neural network (ANN) while texture analysis used Canny edge detection. Experimental results show that the color histogram approach with ANN is better than the texture approach, ie 94% versus 66%. It can be concluded that the freshness of a chicken does not have much effect on the texture of the meat but it has an effect on the color change in the meat.