A sustainable competing dynamic - Real-time Bangla license plate detection and recognition system using YOLOv5 and SSD: A deep learning application. (3rd October 2022)

• Record Type: Journal Article
• Authors: Mehedi Hasan Real, Md; Priya, Anamika Zaman; Alomgir Hossain, Md; Ahmed, Khandakar Rabbi
• Is Part Of: Journal of discrete mathematical sciences & cryptography. Volume 25:Number 7(2022)
• Page Start: 2091
• Page End: 2099
• Publication Date: 2022-10-03
• Subjects: 93C83 -- 68U10; License plate detection -- Bangla -- Deep learning -- Yolo -- Image preprocessing; Computer science -- Mathematics -- Periodicals; Cryptography -- Periodicals; Computer science -- Mathematics; Cryptography; Periodicals; 004.0151
• DOI: 10.1080/09720529.2022.2133248
• Languages: English
• ISSNs: 0972-0529

Abstract

Abstract: In this day and age, the programmed procurement of a tag and acknowledgment assumes a significant part in observing and coordinating vehicles in significant urban communities. It is hard to recognize a driver or proprietor of a vehicle that disregards traffic controls or plays out any incidental movement out and about. It will require a great deal of investment for a cop to review the plate of every vehicle. Subsequently, a mechanized tag acknowledgment framework can tackle these sorts of issues. This is the proposed technique; two Deep Learning calculations are utilized to distinguish the permit number and characters on the tag from the constant picture. The primary YOLOv5 model tracks down the main in the live video of a vehicle out and about. Then, at that point, cut out the area of the permit numbers in the video. The cut casing is then embedded into a second SSD (Single Shot Detection) to identify slugs on that tag. The prepared model acquires a high precision of 96.2% over a sum of 400 picture databases.