CNN models were used to solve pattern recognition and feature extraction problems. In order to classify helmets the
preprocessing step for extracting the area in the image is mostly required before applying CNN. In this paper, an SSD model is
applied to the helmet detection problem.
This model is able to use only one single CNN network to detect the bounding box area of motorcycle and rider. Once the area is
selected we classify whether the biker is wearing or not wearing a helmet at the same time.
Convolutional Neural Network is used to select motorcyclists among the moving objects and recognition of motorcyclists without
a helmet.
