• Amit alhat
• Dattatray Khandelwal

Enforcing use of helmet on every bike-rider is mandatory nowadays due to high accident rate and poor conditioned roads. There are laws regarding safety measures which ensure use of helmet. But currently, they involve manual intervention which is not proven to be so effective because sometimes, bike-riders tend to escape without any penalty after breaking the safety rules like wearing a helmet while riding. Au- tomation is efficient & also a better way to deal with this problem but it comes with its own challenges. To name a few, Low quality image frames (low image resolution, pixel density etc.), rain, dew & fog and partly hidden faces. Hence, the robustness of detection methodology strongly depends on the strength of extracted features and also the ability to deal with the extracted data. The first goal of this project is to boost the potency of helmet detection and then recognizing the license number plate recognition. This model consists of many essential steps developed using today’s most advanced & optimized image processing techniques. This model is a classifi- cation based model that uses supervised learning approach to train the model. The proposed helmet detection model can be used to detect helmet and recognizes license plate even in adverse conditions.

machine learning

"AUTOMATED HELMET DETECTION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.317-328, August-2022, Available :http://www.jetir.org/papers/JETIRFP06056.pdf

"AUTOMATED HELMET DETECTION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. pp317-328, August-2022, Available at : http://www.jetir.org/papers/JETIRFP06056.pdf