Abstract: The success of digital image pattern recognition and feature extraction using a Convolutional Neural Network (CNN) or Deep Learning was recently acknowledged over the years. Researchers have applied these techniques to many problems including traffic offense detection in video surveillance, especially for the motorcycle riders who are not wearing a helmet. Several models of CNN were used to solve these kinds of problem but mostly required the image pre-processing step for extracting the Region of Interest (ROI) area in the image before applying CNN to classify helmet. In this project, we proposed to apply another interesting method of deep learning called Single Shot MultiBox Detector (SSD) into helmet detection problem. This method is the state-of-the-art that is able to use only one single CNN network to detect the bounding box area of motorcycle and rider and then classify that wearing or not wearing a helmet at the same time. The results of the experiment were surprisingly good. the person who are not wearing helmet are detected and stored in the excel sheet and the mail is sent to them.

IndexTerms: CNN,Helmet Detection, Sending Mail

| DOI: 10.17148/IARJSET.2022.9651