Car Number Plate Research Articles

Laporan Akhir Kerja Praktik (KP) Aplikasi Surat Perintah Perjalanan Dinas Di UPTD PPD Medan Utara Bapenda Provsu

The Regional Revenue Agency (BAPEDA) is a government operational support component that carries out financial support tasks in the field of regional income. The author conducted a study of the official travel system while working practically, and at the UPTD PPD North Medan Bapenda PROVSU Medan produced an official travel order application. The author's aim in carrying out this practical work is to support the personnel department in the process of updating employee data including data entry and output. Assist in verifying car number plates and payment of vehicle tax that has just been registered on the e-Samsat application via the website with the branch office. Assist in preparing official travel orders and vehicle transfer reports. After a month of direct practice, the author found many incidents where after discussing with agency superiors, the author discussed the issue of Official Travel Orders (SPPD). The agency will use an inefficient and time-consuming system to handle future cases. because getting permission for official travel requires you to personally navigate a protracted bureaucracy. Therefore, the author used the skills he acquired in college to create an official travel booking system for an agency based on a website, making it easier for the department employees who handle it to obtain permits via the internet only. It can be concluded that students gain new information and experience through practical work that they would not get from face-to-face lectures. A clear picture of the overall scope of activities of an agency is provided through practical work. Additionally, practitioners receive training on how to perform their work with care, diligence, and analysis.

Automatic Car Number Plate Detection System Using OpenCv

bstract: Automatic Number Plate Recognition (ANPR) is an issue that has received a lot of attention and has a lot of successful solutions. Due to the differences in number plate features around the world, these solutions are typically tailored for a specific environment. These attributes are employed in number plate recognition algorithms; thus, a universal solution would be difficult to achieve because the image analysis techniques used to develop these algorithms cannot guarantee 100% accuracy. This research focuses on a proposed method that is optimal for all types of car number plates. The program, which is implemented in Python and uses the OpenCV library, locates the plate by combining edge detection and Feature Detection approaches with mathematical morphology. EasyOCR python package was used to identify the characters on the license plate that were detected.

COMPARISON OF METHODS FOR AUTOMATIC LICENSE NUMBER RECOGNITION

The paper is devoted to the problem of automatic detection and recognition of license plates, the solution of which has many potential applications, from security to traffic management. The purpose of this work was to compare the methods of finding and recognizing car number plates, based on the application of deep learning algorithms, which takes into account different regional standards of car number plates, video quality, different speeds of vehicles, the location of the camera in relation to the vehicle license plate, defects of the car number plate (pollution , deformation), as well as changes in external lighting conditions. The advantages and disadvantages of localization and segmentation of car number plates on cars using image binarization, Viola–Jones and Harr methods are given. It was determined that adaptive approaches are better due to the possibility of compensating the impact of obstacles on different areas of the image, for example, the distribution of shadows due to the heterogeneity of illumination. It was determined that many methods in real algorithms rely directly or indirectly on the presence of number limits. Even if the limits are not used when the number is determined, they have the possibility to be used for further analysis. The methods of templates, image histograms, and contour analysis were compared to identify familiar features in the image (segmentation). It is shown that an effective approach for recognition of car license plates can be based on the application of the methods of Viola-Jones, Harr, the analysis of brightness histograms and the SVM method. Formulated conclusions on the effectiveness of the implementation of each of the procedures were confirmed as a result of conducting experiments with the developed software in the python 3 language using the cv2 computer vision library. The described approach makes it possible to obtain a fairly high recognition accuracy at different angles of rotation of the license plate relative to the camera. Keywords: automatic recognition, license plates, localization, normalization, segmentation, character recognition.

Design and Implementation of an Intelligent Parking System (ISPS) With Laser Security System (LSS)

      In order to solve one of the most important problems, especially in a large and crowded city like Baghdad, is finding an empty and secure car parking space.  In this work, an intelligent Smart Parking System (ISPS) has been investigated and developed by providing information about the empty lots and helping the driver to get to his parking spot with a rotary parking system to reduce the traffic in the parking area. The ISPS Park implements a car number plate recognition system as a security system for car identification. Moreover, for increased security, a fence with a Fiber-Optic vibration system has also been used to prevent any object from entering a parking space without a license. The ISPS was run with the pre-programmed controller to make minimum human involvement in the parking system to ensure access control in restricted places. Matlab with Arduino tools has been used for the car plate number recognition process and car entering control. The system shows that using RFID for entering and leaving is so fast and informative. A Fiber SenSys program has been used with the Alarm Processing Unit (APU) to prevent any unlicensed person from trying to cut, climb or crawl under a fence.

Car number plates recognition system using Advanced Machine learning algorithm

Nowadays in Vietnam, the management of vehicles is extremely complicated. Moreover, the work of detecting and sanctioning traffic violations, anti-theft... have many difficulties. To solve the above problems, it needs automatic systems that perform the job of recognizing plates, capable of reading and understanding plates automatically. That identification system has many practical applications such as automatic vehicle weighing stations, automatic toll stations, and automatic parking lots. As other automation systems, plate recognition involves hardware and software requirements. Hardware is an image acquisition device (camera), the image will be processed by software. The identification includes two stages: plate separation and character recognition. In this paper, a method to recognize car number plates based on an advanced machine-learning algorithm has illustrated to be effective in accurate identification rate in a short time.

License plate detection using YOLO v4

Automatic License Plate Recognition (ALPR) is a sizzling topic in the disciplines of intelligent transportation systems and image recognition. The real-time object detector YOLO (You Only Look Once) - darknet deep learning framework is used in this article to detect car number plates in parking lots in real time. The YOLOv4 deep learning technique was utilized in this proposed strategy to automatically recognize a car's number plate from a video stream. An OCR technique is applied to extract the number from the image of the number plate. The system detects license plates with an accuracy of around 89%.

UHF RFID Tag Design Using Theory of Characteristics Modes for Platform-Tolerant and Harsh Metallic Environments

This paper presents a wideband, long-range RFID tag antenna design with platform tolerant features using characteristic mode analysis (CMA). The proposed design consists of a two-layer structure, that are separated by an air gap. The upper layer consists of T-match and dual loop-based meandered antenna optimized for achieving long read range characteristics in free space/low permittivity dielectrics. The second layer consists of multi-resonant strips printed on a grounded substrate carefully designed using CMA for producing multi-resonant modes in the required UHF RFID band. The multi-resonant strips help in achieving wide bandwidth and isolation between different environment surfaces. This tag antenna provides a wide bandwidth ranging from 900 – 940 MHz that covers both the US UHF RFID band (902 – 928 MHz) and the upper European UHF RFID band (915 – 921 MHz). Moreover, this design achieved a read range of 14.7 m in free space, 14 m on a metal plate, and 13 m on wood, and glass. Furthermore, the proposed antenna was also tested in harsh metal environments such as car number plates and cargo metallic containers. Therefore, the proposed tag can be used for tagging metallic containers, wood containers, and other harsh platforms for cargo management, Asset tracking, supply chain visibility, and Internet of Things (IoT) Applications.

Proposing WPOD-NET combining SVM system for detecting car number plate

<span lang="EN-US">Nowadays, there are many smart parking lots using plate detection system to control in/out vehicles. However, the disadvantages of systems are a fixed environment and necessity of manual labor and requirement of checkpoints in entrances. To solve the problems, a novel algorithm for wide-angle detecting car number plate using warped planar object detection (WPOD-NET) and a modified support vector machine (SVM) system is proposed. Comparing to other models, the proposal improves not only the range of detection angle but also the accuracy of detecting in shady conditions. The results show that the accuracy of proposal model is up to 95.1% with 1000 testing images in various scenarios.</span>

Automatic Car License Plate Detection System: A Review

Automatic license detection system is an essential system in today’s busy traffic system. It helps in automatic monitoring of traffic rules and other law enforcement activities. In India there are many cases of rash driving where in cars violating many traffic rules. It becomes very difficult for traffic policeman to capture the details of the vehicle. Thus, automatic license detection system have been proposed and implemented over the years to help easy and fast monitoring of traffic rules by the vehicles. This paper provides a concise review of various approaches used for automatic license detection system. These approaches can be broadly categorized into two categories: Techniques for automatic car number plate recognition and Techniques for character recognition. This paper also provides advantages and disadvantages of various approaches coming under these categories. Finally, the paper concludes with the comparative result analysis of all approaches reviewed under both the categories.

The Study of Plate Number Recognition for Parking Security System

Car Plate Number Recognition System is an important platform that can be used to identify a car vehicle identity. The Recognition System is based on image processing techniques and computer vision. A webcam is used to capture an image of the car plate number from different distance, and the identification is conducted through four processes of stages: Image Acquisition Pre-processing, Extraction, Segmentation, and Character Recognition. The Acquisition Pre-processing stage is extracted the region of interest of the image. The image is captured by live video of the webcam, then converted to grayscale and binary image. The Extraction stage is extracted the plate number characters from binary image using a connected components method. In the Segmentation stage is done by implementing horizontal projection as well as moving average filter. Lastly, in the Character Recognition, is used to identify the segmented characters of the plate number using optical character recognition. The proposed method is worked well for Malaysian's private cars plate number, and can be implemented in car park system to increase level of security of the system by confirming the bar code of the parking ticket and the plate number of the car at the incoming and outgoing gates.

SECURED PARKING SYSTEM USING IMAGE PROCESSING

From the very beginning, mankind is trying to make their things safe and secure from risk of theft. After reading in depth various results of car thief-ting for last many years, Commonly those cars are been theft in the parking areas where there was no proper system to protect those cars. This work is to minimize the risk of vehicle thief-ting after creating a secured car parking system. If we talk about today's modern world, many of procedures are available to minimize or stop car thief-ting. Our Thesis is based on software and hardware application which works on real time environment. We are adopting the face detection technique under the umbrella of image processing which will provide security for public and parking places, Although we know image processing is a vast field in today’s era. This application uses OpenCV programming language C# using the Haar-cascade and more precisely canny pruning libraries for the detection of facial features. Few years back, list of procedures are adopted just to make a secure car parking system. Some procedures were by adopting RFID and many was by capturing the car number plate under the umbrella of image processing and result of these procedures was, they were failed to secure due to many factors. For example lack of accuracy in character reorganization of number plate and information about driver. However, our system is reliable as the probability of dodging is least, which provides security and flexibility to the car owners.

Improved Alcohol Level Sensing Device that Transmit Offender’s Data to a Central Server through Short Messaging Services (SMS)

This paper is an improved alcohol level sensing system, that measures alcohol intakes, display percentage of alcohol, sound an alarm if alcohol percentage is above the preset thresh hood, documents offender’s data via keypad and transmit same data to a central server with SIM800 GSM/GPRS module via short messaging services for proper documentation and persecution purpose. Here we used an alcohol sensor circuit along with LCD display, a buzzer alarm, ATmega328 microcontroller, keypad and GSM sim module. The system first uses the alcohol sensor in order to detect the alcohol. The sensor provides analog input. These analog inputs are sent to the microcontroller for further processing. The microcontroller calculates the percentage of alcohol from the analog input received and displays the same on the LCD screen. The device was observed to sound an alarm when the percentage of alcohol exceeded the preset value of 0.05 g/mL. Through the use of a 4x4 keypad, documentation of the driver license serial number, the car plate number and name of the driver was achieved. These documented details of the erring driver were transmitted to a preprogrammed mobile phone number via SMS using the SIM800 GSM/GPRS module.

Handwritten Digit Recognition using Image Preprocessing and CNN

Handwritten digit recognition, is a technique of identifying and enlisting the recognized digit, that uses neural networks, deep learning and machine learning. The applications and demand of handwritten digit recognition systems such as zip code recognition, car number plate recognition, robotics, banks, mobile applications and numerous more, are soaring every day. It can be done through numerous approaches, but convolutional neural network is considered one of the best methods. The special neural network uses multilayer architecture for identification and classification. Although the accuracy factor can be increased, based on image preprocessing, in this paper we discuss how the accuracy of the system can be increased for better handwritten digit recognition, using convolutional neural networks, image preprocessing; binarization, resizing, rotation. The accuracy rate obtained is 99.33%.

FEATURES OF THE PREPARATION AND APPOINTMENT OF FORENSIC EXAMINATION OF VEHICLES AND REGISTRATION DOCUMENTS

The article analyzes the features of the preparation and appointment of forensic examination of vehicles, procedural and tactical requirements for this examination. The vehicle is a special object of forensics, which imposes certain restrictions on its preparation for examination.
 Specific requirements for the tactics of investigative actions with this object are intended to ensure the legality and admissibility of evidence for criminal proceedings. The vehicle is also an object for conducting expert studies of various types. The issue of changing the identification numbers (body, engine), determining the year of manufacture, replacing the data carriers about the car (number and code plates, etc.) are resolved by means of traceability. To solve the issue of replacing the body number by replacing the panel with a number plate, a complex forensic chemical (paintwork research) and trace evidence examination are appointed.
 The issue of re-equipment of the vehicle is solved by complex trace evidence and commodity expertise, etc. The complexity of the study of the vehicle and the accompanying documents requires the appointment of directly comprehensive examinations of various types.
 In the investigation of unlawful acts related to the illegal movement of vehicles across the customs border of Ukraine, auto-merchandising and transport- merchandising examinations can also be carried out to solve the problems associated with determining the market value of wheeled vehicles, their components, as well as the amount of the cost of material losses caused to the owner or to the owner of wheeled vehicles, their components due to damage to the latter. The indicated examinations are quite often appointed in conjunction with the trace evidence examination.
 The fulfillment of certain procedural requirements is designed to ensure the legality and admissibility of evidence obtained in the course of investigative actions and the results of forensic examinations conducted by them.

A cloud-based automated parking system for smart campus

Finding a vacant parking space is becoming a real problem especially in areas with limited parking spots such as airports, shopping centres, offices, as well as universities. Searching for available parking slots is normally time consuming and always results in frustration especially when time is the major constraints. Moreover, vacant parking is hard to be noticed due to unsystematic parking system. This will result in longer searching time which can also lead to traffic congestion. In addition, lack of security enforcement on cars entering universities campus is also one of the main issues contributing to insufficient parking spaces. This might cause some unauthorized cars to take opportunity to get inside the campus without any approval and consent from security department. Therefore, A Cloud-based Automated Parking System for Smart Campus is developed in this project. It consists of a sub-system that is developed to display availability number of parking slots so that it will assist authorize users to easily find their parking spots. The proposed system can also recognize car plate number through Automated Car Plate Recognition (ACPR) mechanism which is located at the campus main entrance gate to avoid unauthorized cars from getting in. This has strengthened security level inside campus and ensure the safety of students and staffs. All the information collected are sent into the cloud and stored inside a database system. The information regarding vacant parking can also be displayed using the developed mobile apps.

The use of mathematical morphology and template matching in automatic malaysian car plate number recognition

Car plate number nowadays is an essential component to be recognized because of the useful of its widely application especially in this technological era. Therefore, a method of detection, extraction and recognition of car plate image are important in order to be applied in various applications. Presently, the existing methods have several problems that lead to this study which are high time consuming for training purposes and requirement of complex steps in preparing the whole car plate recognition process. Therefore, the following objectives are set up that are to implement recognition method using Mathematical Morphology and Template Matching on car image which contain plate number. Next, is to evaluate the accuracy of the method. In implementing this study, 25 images data of car with its plate number are collected and used. Mathematical Morphology is used to detect the edge of each character on the car plate while the Template Matching as a tool to match up the detected and template character in order to recognize the registered car plate number. The accuracy of the method is evaluated using percentage recognition rate. Results show that the performance of the method successfully extracted the car plate number area by 92% of the original image. Then for the other of 23 extracted images, it was 86.95% that successfully recognized the number plate. All of these results create its own novelties which are the ability to reduce processing time and having high detection and recognition rate. In conclusion, the proposed method can be one of the alternatives in car plate recognition process in the meanwhile it can be used widely in digital data transfer such as Automatic Enforcement System (AES), automatic saved car park number in smart parking system and high technological verification application of home security system.

Automated Car Number Plate Recognition System using K-Nearest Neighbor

The Automatic number plate recognition (ANPR) is a mass reconnaissance strategy that utilizations optical character recognition on images to peruse the license plates on vehicles. The car number plate detection has the various phases like pre-processing, segmentation and classification. In the previous work, the morphological operation is applied for the car number plate detection. The morphological operation has the low accuracy for the car number plate detection. In the proposed work, the region based segmentation and K-nearest neighbor classification is applied for the character recognition. The proposed is implemented in MATLAB and results are analyzed in terms of accuracy.

In N Go Smart Parking System Integrated with Car Plate Recognition

The smart parking industry around the world continues to evolve due to the advancement of the technology and inadequate parking availability especially in city areas that congested with traffic makes the parking issues become more crucial. Most of the countries around the world trying to improve their parking system to increase the efficiency and effectiveness of the parking mechanism. In N Go is a proposed parking system that integrated with Car Plate Recognition Technology to enhance the parking process to become more efficient. Car Plate Recognition is the key technology of the proposed system that can supported by Mobile Application for ease of information access on parking area, issuing receipts, parking history, parking feedback, manage payment and manage personal account. In N Go system is easy to use by performing 4 easy steps to park, which the first step is to register an account, followed by register car plate number, register a payment and finally maintain registered payment balance. The payment methods used for this system can be either using Credit or Debit card. The benefits of the system is to improve the traditional parking system that still using either receipt or card that is inefficient and this system also can prevent long queues for the payment. Others system functionality are to blast the announcements and penalties to the users. This paper is also highlighting on the conceptual model of the In N Go system.

A Person-Centered Approach to Oncology and Palliative Care

The advent of evidence-based medicine (EBM) saw a marked improvement in clinical decision making when compared to the “this is what works best in my experience” approach, which preceded it. Aside from the fact that there is goodquality evidence available for only a fraction of treatments, a limitation of EBM is that it focuses primarily on identifying the best treatment of a disease and does not allow for differences in patients’ goals, priorities, and expectations or how they cope with their illness. This biomedical focus of EBM is particularly problematic for patients with chronic, incurable illnesses (which include many cancers), for whom a person-centered approach is superior. This article explores what it means to take a person centered approach to oncology and palliative care. In particular, the ambiguity of the term “personalized medicine” in oncology is considered, and seen to be represent a narrow version of “personalized”—in the sense of personalized car number plates and monogrammed shirts—not personalized in the sense of the treatment reflecting the patient’s values, goals, and expectations for care. Furthermore, taking a person-centered approach is an active process that does not equate with acquiescing to whatever the patient requests. As an example, in the emotional, high stakes decision to transition from cancer treatment to palliative care/ hospice or not, patients may reject hospice even when it’s in their best interests (i.e., hospice enrolment). A person-centered physician will understand this situation and attempt to advise the patient to choosing the initially disliked option that may be ultimately the right choice.

Neural Network with Regression Algorithms for Optical Character Recognition

In today's automatic and robust modern world, possibilities of optical character recognition is endless. Previously OCR was used in postal service to read address from mail, car number plate tracking, automation of bank check transfer but today it has taken document management system to whole new level. Using OCR we can convert normal hardcopy document into Searchable text. We will use deep Neural network to train systems to recognise characters in a precise manner, basically we have proposed neural network model combined with machine learning technique like gradientDescent, regression, softmax normalization which will help to increase the efficiency of the OCR. Computer will able to recognise hand written digit. We will be using Google's advanced TensorFlow to create an OCR system which will be efficient and robust in action.