Indian Vehicle Number-Plate Recognition using Single Shot Detection and OCR

Jain, Sparsh; Rathi, R.; Chaurasiya, Rahul Kumar

doi:10.1109/indiscon53343.2021.9582216

Cited by 10 publications

(2 citation statements)

References 8 publications

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“…Over 1200 of these images were discovered in earlier works repositories [17] [18] on Kaggle and GitHub, respectively. Also, 700 pictures were retrieved from another GitHub repository [19]. Fig.…”

Section: Dataset Usedmentioning

confidence: 99%

Chaurah: A Smart Raspberry Pi based Parking System

Choudhaury,

Narendra,

Mishra

et al. 2024

Preprint

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The widespread usage of cars and other large, heavy vehicles necessitates the development of an effective parking infrastructure. Additionally, algorithms for detection and recognition of number plates are often used to identify automobiles all around the world where standardized plate sizes and fonts are enforced, making recognition a effortless task. As a result, both kinds of data can be combined to develop an intelligent parking system centered on ANPR technology. Extraction of the license plate characters from a photo is the primary objective of ANPR. Typically, this procedure is expensive. In this work, we introduce Chaurah, a low-cost Raspberry-Pi 3 based ANPR system designed especially for parking facilities. The system uses two stages of technique, the first of which is an ANPR system that uses two convolutional neural networks (CNNs). The first one uses a vehicle image to find and recognize license plates, while the second one uses optical character recognition to extract the licence plate numbers. The second step of the solution consists of a user-facing application made with Flutter and Firebase for database management in order to compare licence plate records. The app also functions as an interface for a payment system depending on the length of parking time, making it a full software embodiment of the concept.

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Section: Dataset Usedmentioning

confidence: 99%

Chaurah: A Smart Raspberry Pi based Parking System

Choudhaury,

Narendra,

Mishra

et al. 2024

Preprint

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show abstract

“…DenseNet has the benefit of being simple to implement and accurate. In addition to DenseNet, numerous related algorithms, including as MobileNet [41]- [43], Single Shot Detector (SSD) [44]- [46], Yolo [47]- [50], and ResNet [51]- [53], can be used in specific case studies.…”

Section: Artificial Intelligencementioning

confidence: 99%

Indonesian Waste Database: Smart Mechatronics System

Fathurrahman,

Azhari,

Sutikno

et al. 2023

IJRCS

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Waste management is an essential component of urban management. As a waste solution, waste management is critical. The goal of this research is to develop a waste management database that is coupled with a mechatronic robot system. Compiling and gathering data on the sorts of garbage found in Indonesia is the starting point for this research. Indonesian waste is classified into six groups: cardboard, paper, metal, plastic, medical, and organic. The total images of the six groups are estimated at 1880 pictures. According to this picture database, Artificial Intelligence (AI) training was used to create the classification system. In the final AI process, the test method was performed using DenseNet121, DenseNet169, and DenseNet201. Testing using artificial intelligence DenseNet201 across 40 epochs yields the best 92,7% accuracy rate. Simultaneously with Artificial Intelligence testing, a mechatronic system is created as a direct implementation of the Artificial Intelligence output model. A four-servo arm robot with dc motor wheel mobility is included in the mechatronic system. According to these findings, the Indonesian waste database can be categorized correctly using Artificial Intelligence and the mechatronics system. This higher accuracy of the artificial intelligence model may be used to create a waste-sorting robot prototype.

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Identifying the vehicle number plate using deep learning techniques

Theja,

Sridhar

2024

AIP Conference Proceedings

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Indian Vehicle Number-Plate Recognition using Single Shot Detection and OCR

Cited by 10 publications

References 8 publications

Chaurah: A Smart Raspberry Pi based Parking System

Chaurah: A Smart Raspberry Pi based Parking System

Indonesian Waste Database: Smart Mechatronics System

Identifying the vehicle number plate using deep learning techniques

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