• Ahsan Quadri
• Ankush Kumar
• Dr. Nidhi Saxena

The technology of automatic number plate recognition is still in its infancy. This study proposes an automatic number plate identification system for fast-moving automobiles that makes use of security cameras installed along the roadside. Real-time CCTV footage is tough to get. ANPR is an intriguing topic for academics due to its unreliability, climate of the region, and other issues. To make the training process easier, our model employed a deep learning method. Deep-learning techniques are frequently used in the CV sector to strengthen detection results. This scheme provides carparks, personal and public entrances, ticket gates, monitoring, and vehicle registration. This research intends to improve knowledge in ANPR based on Computer Vision(CV) algorithms by recognizing relevant previous work, analyzing and presenting an assessment of extraction, segmentation, and recognition approaches, and offering ideas on future developments in this domain.

ANPR, CV, Deep Learning, TensorFlow, OpenCV, Recognition

"AUTOMATIC NUMBER PLATE RECOGNITION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.c473-c478, May-2022, Available :http://www.jetir.org/papers/JETIR2205359.pdf

"AUTOMATIC NUMBER PLATE RECOGNITION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppc473-c478, May-2022, Available at : http://www.jetir.org/papers/JETIR2205359.pdf