A vision-based machine learning method for barrier access control using vehicle license plate authentication

Automatic vehicle license plate recognition is an essential part of intelligent vehicle access control and monitoring systems. With the increasing number of vehicles, it is important that an effective real-time system for automated license plate recognition is developed. Computer vision techniques are typically used for this task. However, it remains a challenging problem, as both high accuracy and low processing time are required in such a system. Here, we propose a method for license plate recognition that seeks to find a balance between these two requirements. The proposed method consists of two stages: detection and recognition. In the detection stage, the image is processed so that a region of interest is identified. In the recognition stage, features are extracted from the region of interest using the histogram of oriented gradients method. These features are then used to train an artificial neural network to identify characters in the license plate. Experimental results show that the proposed method achieves a high level of accuracy as well as low processing time when compared to existing methods, indicating that it is suitable for real-time applications

Cyber-physical system based on image recognition to improve traffic flow: A case study

Vehicular traffic in metropolitan areas turns congested along either paths or periods. As a case study, we have considered a mass transport system with a bus fleet that rides over exclusive lanes across streets and avenues in an urban area that does not allow the circulation of lightweight vehicles, cargo, and motorcycles. This traffic flow becomes congested due to the absence of restriction policies based on criteria. Moreover, the exclusive lanes are at ground level, decreasing lanes for other vehicles. The main objective of this proposal consists of controlling the access to the exclusive lanes by a cyber-physical system following authorization conditions, verifying the permission status of a vehicle by the accurate recognition of license plates to reduce traffic congestion. Therefore, in the case of invading an exclusive lane without permission, the vehicle owner gets a notification of the fine with the respective evidence

Automated License Plate Recognition using Existing University Infrastructure and Different Camera Angles

Number or license plate recognition has become an essential technology for traffic and security applications. Providing access control at any organization or academic institution improves the level of security. However, providing security personnel to manually control the access of vehicles at an academic institution is costly, time-consuming, and to a limited extent, error prone. This study investigated the use of an automated vehicle tracking system, incorporating experimental computer vision techniques for license plate recognition that runs in real-time to provide access control for vehicles and provide increased security for an academic institution. A vehicle monitoring framework was designed by using various technologies and experimenting with different camera angles. In addition, the effect of environmental changes on the accuracy of the optical character recognition application was assessed. The Design Science Research methodology was followed to develop the vehicle monitoring framework artifact. Image enhancement algorithms were tested, and the most viable options were evaluated and implemented. Optimal operating criteria that were established for the vehicle monitoring framework achieved a 96% success rate. The results indicate that a cost-effective solution could be provided by using an existing camera infrastructure at an academic institution and suitable license plate recognition software technologies, algorithms, and different camera angles

Comparative analysis of Tesseract and Google Cloud Vision for Thai vehicle registration certificate

Optical character recognition (OCR) is a technology to digitize a paper-based document to digital form. This research studies the extraction of the characters from a Thai vehicle registration certificate via a Google Cloud Vision API and a Tesseract OCR. The recognition performance of both OCR APIs is also examined. The 84 color image files comprised three image sizes/resolutions and five image characteristics. For suitable image type comparison, the greyscale and binary image are converted from color images. Furthermore, the three pre-processing techniques, sharpening, contrast adjustment, and brightness adjustment, are also applied to enhance the quality of image before applying the two OCR APIs. The recognition performance was evaluated in terms of accuracy and readability. The results showed that the Google Cloud Vision API works well for the Thai vehicle registration certificate with an accuracy of 84.43%, whereas the Tesseract OCR showed an accuracy of 47.02%. The highest accuracy came from the color image with 1024×768 px, 300dpi, and using sharpening and brightness adjustment as pre-processing techniques. In terms of readability, the Google Cloud Vision API has more readability than the Tesseract. The proposed conditions facilitate the possibility of the implementation for Thai vehicle registration certificate recognition system

From banal surveillance to function creep: automated license plate recognition (ALPR) in Denmark

This article discusses how Automated License Plate Recognition (ALPR) has been implemented in Denmark across three different sectors: parking, environmental zoning, and policing. ALPR systems are deployed as a configuration of cameras, servers, and algorithms of computer vision that automatically reads and records license plates of passing cars. Through digital ethnography and interviews with key stakeholders in Denmark, we contribute to the fields of critical algorithm and surveillance studies with a concrete empirical study on how ALPR systems are configured according to user-specific demands. Each case gives nuance to how ALPR systems are implemented: (1) how the seamless charging for a “barrier-free” parking experience poses particular challenges for customers and companies; (2) how environmental zoning enforcement through automated fines avoids dragnet data collection through customized design and regulation; and (3) how the Danish Police has widened its dragnet data collection with little public oversight and questionable efficacy. We argue that ALPR enacts a form of “banal surveillance” because such systems operate inconspicuously under the radar of public attention. As the central analytic perspective, banality highlights how the demand for increasing efficiency in different domains makes surveillance socially and politically acceptable in the long run. Although we find that legal and civic modes of regulation are important for shaping the deployment of ALPR, the potential for function creep is embedded into the very process of infrastructuring due to a lack of public understanding of these technologies. We discuss wider consequences of ALPR as a specific and overlooked instance of algorithmic surveillance, contributing to academic and public debates around the embedding of algorithmic governance and computer vision into everyday life

Vehicular sensor networks: Applications, advances and challenges

Vehicular sensor networks (VSN) provide a new paradigm for transportation technology and demonstrate massive potential to improve the transportation environment due to the unlimited power supply of the vehicles and resulting minimum energy constraints. This special issue is focused on the recent developments within the vehicular networks and vehicular sensor networks domain. The papers included in this Special Issue (SI) provide useful insights to the implementation, modelling, and integration of novel technologies, including blockchain, named data networking, and 5G, to name a few, within vehicular networks and VSN.N/

Concept of an Intelligent Parking System; Efforts to Resolve Traffic Conflicts Regulations

Makassar, an Indonesian city, is situated on the south-western coast of Sulawesi Island. It is the largest commercial centre in eastern Indonesia, and traffic congestion is a problem there. Movement management must establish sufficient and well-organized parking areas, as well as a good and transparent system to eliminate unmonitored restitution funds, in order to address these issues. To address parking issues in Makassar, a legal and technical strategy is developed, with an emphasis on inclusiveness and including both legal and illegal parking spaces. The integrated parking concept is comprised of a mobile, everywhere-accessible parking area reservation system, a vehicle registration system based on licence plate numbers, and an effective data management system. 180 million Indonesian Rupiah are spent on all equipment and activity installations (IDR). At least 50 locations utilising this system will be required for a minimum vehicle range of 250,000 units, resulting in an approximate capital cost of 9 billion rupiah. The first clause describes the application of minimum parking fees to flat parking fees (generally 2 thousand rupiah). During a single parking period, it is anticipated that 250,000 vehicles will utilise this parking system if all parking spaces are occupied simultaneously. Government and investors can raise 250 million rupiah in investment capital assuming a 50:50 profit split. Revenue can reach billions of rupiah with just four iterations. Doi: 10.28991/CEJ-SP2023-09-05 Full Text: PD

Development Of A Virtual Vehicle Identification For Tracking Hit-And-Run Vehicle

In general, the vehicle registration plate number and the witness are essential clues for police investigating hit-and-run accidents. Without these clues, it will be difficult for police to trace the suspect and lead to a closed case even though a fatal victim is involved. In this work, the virtual vehicle identification tracking system is developed by using wireless communication interfaces to transfer useful data for road accidents and traffic surveillance. This system uses vehicle access points and employs Vehicular Ad Hoc Network (VANET) to assist the vehicle identity tracking system. The Internet of Things (IoT) development board scans all the vehicle Wi-Fi access points within the beacon frames. With the characteristics of different positions of signal strength and the distance of station to access point, it is difficult to accurately determine the offender's vehicle identity. Hence, this paper purposes a hybrid tracking method to combine pre accident and post-accident tracking methods to track vehicle identity. Moreover, this report shows unique Wi-Fi access point identities such as Service Set Identifier (SSID) and Media Access Control (MAC) addresses can be used as virtual vehicle identities for vehicle tracking and traffic surveillance systems. Overall, the result shows this system can track the suspect vehicle's identity with positive detection. When both accelerometers detect the impact acceleration above 4G or 39.24 m/s2 , the transmitter IoT board is activated and exchanges the 32 bytes of packet with another transmitter. The maximum distance for the system to track vehicle access point signal is up to 45 meters and it is workable above 50 km/h of driving speed

International overview on the legal framework for highly automated vehicles

The evolution of Autonomous and automated technologies during the last decades has been constant and maintained. All of us can remember an old film, in which they shown us a driverless car, and we thought it was just an unreal object born of filmmakers imagination. However, nowadays Highly Automated Vehicles are a reality, even not in our daily lives. Hardly a day we don’t have news about Tesla launching a new model or Google showing the new features of their autonomous car. But don’t have to travel far away from our borders. Here in Europe we also can find different companies trying, with more or less success depending on with, not to be lagged behind in this race. But today their biggest problem is not only the liability of their innovative technology, but also the legal framework for Highly Automated Vehicles. As a quick summary, in only a few countries they have testing licenses, which not allow them to freely drive, and to the contrary most nearly ban their use. The next milestone in autonomous driving is to build and homogeneous, safe and global legal framework. With this in mind, this paper presents an international overview on the legal framework for Highly Automated Vehicles. We also present de different issues that such technologies have to face to and which they have to overcome in the next years to be a real and daily technology

Second Line of Defense: Electronic Maintenance Reports, Local Maintenance Provider User Guide, Rev. 3

The Electronic Maintenance Report forms allow Local Maintenance Providers (LMP) and other program staff to enter maintenance information into a simple and secure system. This document describes the features and information required to complete the Maintenance Report forms. It is expected that all Corrective Maintenance Reports from LMPs will be submitted electronically into the SLD Portal. As an exception (e.g., when access to the SLD Portal is unavailable), Maintenance Reports can be submitted via a secure Adobe PDF form available through the Sustainability Manager assigned to each country