Segmenting characters from license plate images with little prior knowledge

Wenjing Jia; Xiangjian He; Qiang Wu

doi:10.1109/DICTA.2010.48

Segmenting characters from license plate images with little prior knowledge

Wenjing Jia^*
, Xiangjian He
, Qiang Wu

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

In this paper, to enable a fast and robust system for automatically recognizing license plates with various appearances, new and simple but efficient algorithms are developed to segment characters from extracted license plate images. Our goal is to segment characters properly from a license plate image region. Different from existing methods for segmenting degraded machine-printed characters, our algorithms are based on very weak assumptions and use no prior knowledge about the format of the plates, in order for them to be applicable to wider applications. Experimental results demonstrate promising efficiency and flexibility of the proposed scheme.

Original language	English
Title of host publication	Proceedings - 2010 Digital Image Computing
Subtitle of host publication	Techniques and Applications, DICTA 2010
Publisher	IEEE Computer Society
Pages	220-226
Number of pages	7
ISBN (Print)	9780769542713
DOIs	https://doi.org/10.1109/DICTA.2010.48
Publication status	Published - 2010
Externally published	Yes

Publication series

Name	Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Science Applications

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10.1109/DICTA.2010.48

Cite this

Jia, W., He, X., & Wu, Q. (2010). Segmenting characters from license plate images with little prior knowledge. In Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010 (pp. 220-226). Article 5692568 (Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010). IEEE Computer Society. https://doi.org/10.1109/DICTA.2010.48

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title = "Segmenting characters from license plate images with little prior knowledge",

abstract = "In this paper, to enable a fast and robust system for automatically recognizing license plates with various appearances, new and simple but efficient algorithms are developed to segment characters from extracted license plate images. Our goal is to segment characters properly from a license plate image region. Different from existing methods for segmenting degraded machine-printed characters, our algorithms are based on very weak assumptions and use no prior knowledge about the format of the plates, in order for them to be applicable to wider applications. Experimental results demonstrate promising efficiency and flexibility of the proposed scheme.",

author = "Wenjing Jia and Xiangjian He and Qiang Wu",

year = "2010",

doi = "10.1109/DICTA.2010.48",

language = "English",

isbn = "9780769542713",

series = "Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010",

publisher = "IEEE Computer Society",

pages = "220--226",

booktitle = "Proceedings - 2010 Digital Image Computing",

address = "United States",

}

Segmenting characters from license plate images with little prior knowledge. / Jia, Wenjing; He, Xiangjian; Wu, Qiang.
Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010. IEEE Computer Society, 2010. p. 220-226 5692568 (Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Segmenting characters from license plate images with little prior knowledge

AU - Jia, Wenjing

AU - He, Xiangjian

AU - Wu, Qiang

PY - 2010

Y1 - 2010

N2 - In this paper, to enable a fast and robust system for automatically recognizing license plates with various appearances, new and simple but efficient algorithms are developed to segment characters from extracted license plate images. Our goal is to segment characters properly from a license plate image region. Different from existing methods for segmenting degraded machine-printed characters, our algorithms are based on very weak assumptions and use no prior knowledge about the format of the plates, in order for them to be applicable to wider applications. Experimental results demonstrate promising efficiency and flexibility of the proposed scheme.

AB - In this paper, to enable a fast and robust system for automatically recognizing license plates with various appearances, new and simple but efficient algorithms are developed to segment characters from extracted license plate images. Our goal is to segment characters properly from a license plate image region. Different from existing methods for segmenting degraded machine-printed characters, our algorithms are based on very weak assumptions and use no prior knowledge about the format of the plates, in order for them to be applicable to wider applications. Experimental results demonstrate promising efficiency and flexibility of the proposed scheme.

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U2 - 10.1109/DICTA.2010.48

DO - 10.1109/DICTA.2010.48

M3 - Conference contribution

AN - SCOPUS:79951642845

SN - 9780769542713

T3 - Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010

SP - 220

EP - 226

BT - Proceedings - 2010 Digital Image Computing

PB - IEEE Computer Society

ER -

Segmenting characters from license plate images with little prior knowledge

Abstract

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ASJC Scopus subject areas

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