A method for identifying specific vehicles using template matching

Yamaguchi, Kazuo; Nagaya, Yoshiaki; Ueda, Keigo; Nemoto, Hiromi; Nakagawa, Masao

doi:10.1109/itsc.1999.821019

Cited by 23 publications

(11 citation statements)

References 1 publication

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“…Automatic license plate recognition plays an important role in numerous real-life applications, such as unattended parking lots [1], [2], security control of restricted areas [3], traffic law enforcement [4]- [6], congestion pricing [7], and automatic toll collection [8], [9]. In the most of present methods, the conditions of environment and plate, effect on the performance of the method, therefore these methods have limitations.…”

Section: Introductionmentioning

confidence: 99%

New framework based on complementary methods for efficiency and accuracy of license plate recognition system

Azad

Davami

Jeo

et al. 2014

2014 6th Conference on Information and Knowledge Technology (IKT)

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This paper represents a new and intelligent system for license plate recognition used in many cases, for example: unattended parking lots, security control of restricted areas, traffic law enforcement, congestion pricing, and automatic toll collection. The proposed system is a process based on a combination of the complement methods that increases the accuracy of output data and is generally accountable on the images that have many problems and aren't answerable with a particular approach. The performance of this system is in a form that, firstly, the input image is given to all the complement methods in order for the location of the plate candidate to be determined, then their response is investigated according to the valence function and finally the location of plate is properly determined by the majority of votes and ensures the accuracy of output data. If the complement methods are chosen correctly, this proposed system will be responsive to the images in which the license plate recognition is likely. This method has been tested on two data sets that have different images of the background, considering the distance, and angle of view so that the correct extraction rate of plate location reached at 100% and 99% respectively.

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Section: Introductionmentioning

confidence: 99%

New framework based on complementary methods for efficiency and accuracy of license plate recognition system

Azad

Davami

Jeo

et al. 2014

2014 6th Conference on Information and Knowledge Technology (IKT)

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“…Nowadays LPR has been used in different applications such as parking lots [1], automatic toll collection [2], traffic law enforcement [3] and many others. LPR mainly consists of three stages: license plate location(LPL), character extraction and character recognition.…”

Section: Introductionmentioning

confidence: 99%

A license plate recognition system based on tamura texture in complex conditions

Zhang

Shen

Gao

et al. 2010

The 2010 IEEE International Conference on Information and Automation

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License plate location plays an important role in vehicle license plate recognition. This paper presents a real time method of license plate location. First, run length is used for finding the candidate horizontal regions of license plate. Second, we locate the license plates exactly using tamura texture features. In the experiment on locating license plates, 1400 images were taken in various backgrounds and complex conditions. Experimental results showed the robustness and efficiency of the method presented in this paper.Index Terms-Run length, Tamura texture, LPR algorithm G(i, j) = 0.

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“…Automatic vehicle recognition is an important part of numerous applications such as traffic law enforcement [1], automatic toll collection [2], and traffic control in restricted areas [3]. Although these systems emerged in 80s [4] and commercially used from 90s [5], their use in Iran is restricted due to various difficulties in using LPR systems for Farsi license plates [6].…”

Section: Introductionmentioning

confidence: 99%

Enhancing automatic speed estimation systems performance using support vector machines

Viand

Seyedjavadi

Rahmani

2009

2009 IEEE 5th International Conference on Intelligent Computer Communication and Processing

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Speed cameras are systems which normally include a camera, a calibration system, speed estimation software, and a vehicle recognition system (which includes a vehicle type detector and a LPR system). These systems are normally used to detect and identify vehicles disobeying a speed limit in a road. While these systems are used widely in the world, their use in Iran is restricted due to various difficulties in using LPR systems for Farsi license plates. Also, to reduce the setup cost, in many traffic law enforcement systems low-cost low-resolution IR cameras are used, which increases the LPR complexity. In this paper, it has been showed that how using statistical learning methods (specifically SVMs) enhanced the automatic speed estimation systems performance by improving the vehicle identification via reading the license plate. The focus will be on Farsi license plates recognition. Obviously the results can be used in many potential applications such as automatic toll collection and traffic control in restricted areas.978-1-4244-5007-7/09/$26.00 ©2009 IEEE

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A method for identifying specific vehicles using template matching

Cited by 23 publications

References 1 publication

New framework based on complementary methods for efficiency and accuracy of license plate recognition system

New framework based on complementary methods for efficiency and accuracy of license plate recognition system

A license plate recognition system based on tamura texture in complex conditions

Enhancing automatic speed estimation systems performance using support vector machines

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