An Efficient Features - Based License Plate Localization Method

Mahini, Hamid; Kasaei, Shohreh; Dorri, Fatemeh

doi:10.1109/icpr.2006.239

Cited by 80 publications

(40 citation statements)

References 7 publications

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“…The proposed system is developed using VC++ and QT [16,20]. QT is a comprehensive C++ application development framework for creating cross-platform GUI applications.…”

Section: Resultsmentioning

confidence: 99%

“…This requires the location algorithm to be insensitive to noise, illumination changes, LP defects, skew, deformation and other adverse conditions. Here we study, discuss and compare with several LP location algorithms as follows: method based on linear detection, method based on grayscale edge detection, method based on morphology, method based on texture feature [15], and method based on color feature [16]. Table 1 shows the different performances of these LP location algorithms.…”

Section: Lpr Algorithmmentioning

confidence: 99%

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Design of Intelligent Parking Management System Based on License Plate Recognition

Tian

Guo

Qiao

et al. 2014

JMM

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Abstract-License Plate Recognition (LPR) which has been extensively studied recently is becoming one important part of Intelligent Transportation Systems (ITS). It is not only applied to public security monitoring, but also applied to a red light shot, speeding violation paparazzi, parking system and so on. The present paper introduces an intelligent parking management system based on LPR, recognizing license plate automatically at the parking lot access and realizing vehicle information integrated management conveniently. The software part is developed with VC++, QT and Microsoft Office Access Database. In the system, LPR is carried out through video streaming frame by frame to choose the best result with a high speed. After accurate LPR, the vehicle information, such as LP number, LP color, car type and access time, will be stored in system database. In addition, the system interface is designed very friendly and simple for administrators to operate, which can largely improve the whole performance of LPR system. Experimental results show that this parking management system can achieve high correct rate at 95%, and can be applied to real-time implementation.

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“…The proposed system is developed using VC++ and QT [16,20]. QT is a comprehensive C++ application development framework for creating cross-platform GUI applications.…”

Section: Resultsmentioning

confidence: 99%

Section: Lpr Algorithmmentioning

confidence: 99%

Design of Intelligent Parking Management System Based on License Plate Recognition

Tian

Guo

Qiao

et al. 2014

JMM

View full text Add to dashboard Cite

show abstract

“…The value of each pixel at output of a morphological filter is determined based on the value of corresponding pixel and a specified neighborhood of it in input image. Based on the size and shape of the considered neighborhood, one can define a morphological operation which is sensitive to specific shapes [15].…”

Section: License Plate Extraction Using Morphological Processingmentioning

confidence: 99%

An edge-based color-aided method for license plate detection

Abolghasemi

Ahmadyfard

2009

Image and Vision Computing

142

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“…Another used method applied to binary images for CS is CCA which is based on some geometric conditions where height, width, and area of characters need to be measured [74][75][76][77][78][79]. In this method the correct position of each character can be extracted even if the 24 NP is inclined, but it requires each character to be fully connected and neighboured characters must not be connected.…”

Section: Horizontal Projectionmentioning

confidence: 99%

Automatic Number Plate Recognition on FPGA

Zhai

Bensaali

McDonald-Maier

2013

2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS)

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Automatic Number Plate Recognition on FPGA i AbstractIntelligent Transportation Systems (ITSs) play an important role in modern traffic management, which can be divided into intelligent infrastructure systems and intelligent vehicle systems. Automatic Number Plate Recognition systems (ANPRs) are one of infrastructure systems that allow users to track, identify and monitor moving vehicles by automatically extracting their number plates. ANPR is a well proven technology that is widely used throughout the world by both public and commercial organisations. There are a wide variety of commercial uses for the technology that include automatic congestion charge systems, access control and tracing of stolen cars. The fundamental requirements of an ANPR system are image capture using an ANPR camera and processing of the captured image. The image processing part, which is a computationally intensive task, includes three stages: Number Plate Localisation (NPL), Character Segmentation (CS) and Optical Character Recognition (OCR). The common hardware choice for its implementation is often high performance workstations. However, the cost, compactness and power issues that come with these solutions motivate the search for other platforms. Recent improvements in low-power high-performance Field Programmable Gate Arrays (FPGAs) and Digital Signal Processors (DSPs) for image processing have motivated researchers to consider them as a low cost solution for accelerating such computationally intensive tasks.Current ANPR systems generally use a separate camera and a stand-alone computer for processing. By optimising the ANPR algorithms to take specific advantages of technical features and innovations available within new FPGAs, such as low power consumption, development time, and vast on-chip resources, it will be possible to replace the high performance roadside computers with small in-camera dedicated platforms. In spite of this, costs associated with the computational resources required for complex algorithms together with limited memory have hindered the development of embedded vision platforms.The work described in this thesis is concerned with the development of a range of image The overall results achieved show that the entire ANPR system can be implemented on a single FPGA that can be placed within an ANPR camera housing to create a stand-alone unit. As the benefits of this are drastically improve energy efficiency and removing the need for the installation and cabling costs associated with bulky PCs situated in expensive, cooled, waterproof roadside cabinets. Certificate of OriginalityAutomatic Number Plate Recognition on FPGA iii Certificate of OriginalityI hereby certify that the work presented in this report is my original research and has not been presented for a higher degree at any other university or institute.

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An Efficient Features - Based License Plate Localization Method

Abstract: Abstract

Cited by 80 publications

References 7 publications

Design of Intelligent Parking Management System Based on License Plate Recognition

Design of Intelligent Parking Management System Based on License Plate Recognition

An edge-based color-aided method for license plate detection

Automatic Number Plate Recognition on FPGA

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