Detection of Two wheeler Driver Safety Using Machine Learning
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 6, Pages 2292-2298
AbstractThe most common type of transportation in India is two-wheeler, where the number of accidents are increasing day-by-day. In general, these accidents have occurred due to riding a motorcycle without a helmet. It is very difficult to monitor each and every rider whether they are wearing a helmet or not, by a human labor, where as an electronic detection system can do the same kind of work without any human effort. Image processing is a solution for this kind of problem where there are many advancements in recent times. This works with extracting the features and identifying the objects which resides in the images which are taken out from the video surveillance as multiple frames. Convolutional Neural Networks (CNN) or Deep learning techniques are used for image or pattern identification along with Visual Geometry Group (VGG) which is mainly used for object detection. If a bike rider is found travelling without a helmet, the image of the number plate of the bike is captured. The number plate is checked with the databases and penalty will be issued. The system uses pure machine learning algorithm for image processing. Identification of the motorcycle can be done in five steps: image capturing, pre-processing of image, finding the errors, image recognition, and feature extraction.
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