Automatic RoI dan Active Contour untuk Deteksi Penggunaan Helm pada Pengendara Sepeda Motor - widiawati, chyntia raras ajeng (Universitas Trilogi, 2019)
Based on data from the Central Statistics Agency, motorcycle accidents are the most common accidents and many contribute to the death rate in traffic accidents. Some cases of deaths in motorcycle accidents are caused by riders not wearing helmets. Monitoring via CCTV video has been done but it takes a long time so we need another solution to be more effective. Some techniques have been carried out including detection of the use of helmets on motorcyclists by using digital image processing. Some previous studies on these cases experienced obstacles such as overlapping images in the identification process. This study aims to develop a detection method that focuses on the segmentation stage to produce a better segmentation image. The method used in this study is Automatic RoI and Active Contour at the segmentation stage which is then classified using the Multilayer Perceptron classifier. The results obtained give an accuracy value of 72.97%, a sensitivity of 76.19% and a specificity of 68.75%.