Helmet Violation Processing for Law Enforcement using CCTV Camera

<div&gt;The rising number of traffic rule violators, as well as the resulting mishaps,</div&gt;<div&gt;has made road safety a major concern. Detection of traffic rule violators is challenging&lt;/div&gt;<div&gt;due to various difficulties such as occlusion, illumination, poor quality of surveillance&lt;/div&gt;<div&gt;video, varying weather conditions, etc. The existing surveillance systems are primarily&lt;/div&gt;<div&gt;dependent on the performance of human operators who are unrealistically expected to&lt;/div&gt;<div&gt;simultaneously watch many screens that show streams captured by different cameras.</div&gt;<div&gt;The task of these operators is becoming more difficult as the number of simultaneous&lt;/div&gt;<div&gt;video streams to watch increases. It is well-known that after twenty minutes of&lt;/div&gt;<div&gt;continuous work, the operator's attention degrades significantly. Thus, there is a need&lt;/div&gt;<div&gt;for an automatic detection system. This research aims to increase the installations of&lt;/div&gt;<div&gt;new cameras covering more areas. It will help overcome all the difficulties mentioned&lt;/div&gt;<div&gt;above and ensure motorcyclists' detection without helmets using the CCTV cameras'</div&gt;<div&gt;footage and machine learning algorithms. It will help law enforcement by police and&lt;/div&gt;<div&gt;eventually change the risk behaviors of motorcyclists. Consequently, the number of&lt;/div&gt;<div&gt;accidents and their severity will reduce.</div&gt;