Fish Genus Classification System Using Viola-Jones Feature Extraction and Boosting Based on Decision Tree

The fisheries cultivation sector in Indonesia is an economic sector that has great value for the Indonesian people's economy, but this sector still has quite a big problem in fish classification. In this study, the author uses the Viola-Jones Feature Extraction and Boosting Based on Decision Tree to classify fish. The first step in this method is to train a weak classifier to classify several features of several classes of fish, followed by Boosting, and creating a cascade to speed up the classification process. The result of this process is a program that can classify and annotate fish based on image input.