Arc Circularitie Naive Bayes for Occupational Safety Helmet Detection

Abstract

Occupational Safety and Health (OHS) is an effort to guarantee and protect the safety and health of every worker through efforts to prevent work accidents and work-related diseases. Safety Helmet is one of the components that must exist and be used in accordance with Occupational Safety and Health standards. Detection of safety helmets usage is one of the efforts to support these activities. The application of Arc Circularity Naive Bayes is used to detect whether an object meets the ratio of a circle by utilizing RGB and HSV image filtering and classification using Naïve Bayes. That method is used to detect whether a worker uses a safety helmet or not, it also detects helm color. The average value of accuracy is 50.8, precision is 58.3%, recall is 66.0%, and f1-score is 59.5% which are calculated using the Confusion Matrix