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All Journal International Journal of Electrical and Computer Engineering
Pattar, Ramakanth Kumar
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Computer Science & IT Electrical & Electronics Engineering

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Enhancing automatic license plate recognition in Indian scenarios Samaga, Abhinav; Lobo, Allen Joel; Nasreen, Azra; Pattar, Ramakanth Kumar; Trivedi, Neeta; Raj, Peehu; Sreelakshmi, Koratagere
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp365-373

Abstract

Automatic license plate recognition (ALPR) technology has gained widespread use in many countries, including India. With the explosion in the number of vehicles plying over the roads in the past few years, automating the process of documenting vehicle license plates for use by law enforcement agencies and traffic management authorities has great significance. There have been various advancements in the object detection, object tracking, and optical character recognition domain but integrated pipelines for ALPR in Indian scenarios are a rare occurrence. This paper proposes an architecture that can track vehicles across multiple frames, detect number plates and perform optical character recognition (OCR) on them. A dataset consisting of Indian vehicles for the detection of oblique license plates is collected and a framework to increase the accuracy of OCR using the data across multiple frames is proposed. The proposed system can record license plate readings of vehicles averaging 527.99 and 2157.09 ms per frame using graphics processing unit (GPU) and central processing unit (CPU) respectively.
Architectural trade-offs: comparative analysis across K3s, serverless, and traditional server deployments P., Prajwal; Teli, Naveen B.; H. N., Nishal; Dey, Nimisha; Deenadhayalan, Pratiba; Pattar, Ramakanth Kumar; Hadagali, Pavithra; P. R., Skanda
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i2.pp873-882

Abstract

In modern software architecture, combining serverless computing, microservices, and containers improves scalability, performance, observability, and resilience. However, choosing the right deployment strategy is crucial. Current individual deployment methods often limit productivity because of poor integration options. This study looks at three deployment approaches: Kubernetes cluster, AWS Lambda (serverless), and Traditional Java Server. We tested performance under different workloads using virtual machines and simulations. The results show that the K3s cluster provides high throughput and low latency because it manages resources directly. AWS Lambda’s pay-as-you-go model, along with its built-in cost optimization, works well for event-driven workloads. In contrast, Java Microservice is cost-effective but needs manual tuning to control latency and error rates. Bringing these scenarios together into a single service mesh architecture could help optimize costs, performance, and system resilience.
Co-Authors Deenadhayalan, Pratiba Dey, Nimisha H. N., Nishal Hadagali, Pavithra Lobo, Allen Joel Nasreen, Azra P. R., Skanda P., Prajwal Raj, Peehu Samaga, Abhinav Sreelakshmi, Koratagere Teli, Naveen B. Trivedi, Neeta