Deep Learning Algorithm as an Alternative of Automatic Classification of Dirty Eggs

Abstract

Egg, which is one of the daily needs, contains important nutrition like protein, vitamins, mineral and 75 Kcal. Thus, one of the external qualities of eggs becomes one of the considerations in determining egg quality. The poor condition of the egg shell can be unhealthy and harmful. The dirty eggs and the clean ones are important elements in an automatic separation system since they relate to the consumer’s economic and health values. An element such as dirt at the eggshell leads the raise of Salmonella bacteria and will be worse if the bacteria get into the eggshell. An automatic method of egg selection is crucial to determining the egg's quality before it reaches the consumer. Selecting and classifying egg manually is inefficient for the seller, due to it takes more time and complicated processes. The development of an automatic method is required to categorize and simplify the manual system. Deep Learning Algorithm become one of remarkable solution in developing the method of classification and qualified egg. The method of deep learning algorithms is a computational process that is simpler than other computing methods. The process of egg selection is conducted based on the dirtiness of the eggs. The result of this system is able to classify accurately and efficiently to the select whether the egg has good or bad quality, in order to simplify the breeders’ job.