An approach to detection and location for license plate based on modified HSI color model

Xiao Fang Liu; Dan Song Cheng; Jia Feng Liu; Ning Guan

An approach to detection and location for license plate based on modified HSI color model

Xiao Fang Liu^*
, Dan Song Cheng
, Jia Feng Liu
, Ning Guan

^*Corresponding author for this work

School of Electrical Engineering and Automation, Harbin Institute of Technology
School of Computer Science and Technology, Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

In order to improve the performance of license plate recognition system, an advanced approach to the detection of the License Plate based on the Modified HSI color model is proposed. According to the actual situation of recognizing license plate, the ANN (Annual Neural Network) and projecting algorithm are applied to detect and locate the license plate in the video image by using the texture features of the transformed image. The test shows the location accuracy rate for static images is 98%, detection rate of plate is 91%, and processing rate is 0.032 second per frame, which meets the requirements of processing rate in real-time system.

Original language	English
Pages (from-to)	85-89
Number of pages	5
Journal	Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology
Volume	40
Issue number	1
State	Published - Jan 2008
Externally published	Yes

Keywords

ANN
Characteristic region combination
HSI color model
License diction and plate

Cite this

@article{a95722932211403b978ca2a8a3d28a4e,

title = "An approach to detection and location for license plate based on modified HSI color model",

abstract = "In order to improve the performance of license plate recognition system, an advanced approach to the detection of the License Plate based on the Modified HSI color model is proposed. According to the actual situation of recognizing license plate, the ANN (Annual Neural Network) and projecting algorithm are applied to detect and locate the license plate in the video image by using the texture features of the transformed image. The test shows the location accuracy rate for static images is 98\%, detection rate of plate is 91\%, and processing rate is 0.032 second per frame, which meets the requirements of processing rate in real-time system.",

keywords = "ANN, Characteristic region combination, HSI color model, License diction and plate",

author = "Liu, \{Xiao Fang\} and Cheng, \{Dan Song\} and Liu, \{Jia Feng\} and Ning Guan",

year = "2008",

month = jan,

language = "英语",

volume = "40",

pages = "85--89",

journal = "Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology",

issn = "0367-6234",

publisher = "Harbin Institute of Technology",

number = "1",

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TY - JOUR

T1 - An approach to detection and location for license plate based on modified HSI color model

AU - Liu, Xiao Fang

AU - Cheng, Dan Song

AU - Liu, Jia Feng

AU - Guan, Ning

PY - 2008/1

Y1 - 2008/1

N2 - In order to improve the performance of license plate recognition system, an advanced approach to the detection of the License Plate based on the Modified HSI color model is proposed. According to the actual situation of recognizing license plate, the ANN (Annual Neural Network) and projecting algorithm are applied to detect and locate the license plate in the video image by using the texture features of the transformed image. The test shows the location accuracy rate for static images is 98%, detection rate of plate is 91%, and processing rate is 0.032 second per frame, which meets the requirements of processing rate in real-time system.

AB - In order to improve the performance of license plate recognition system, an advanced approach to the detection of the License Plate based on the Modified HSI color model is proposed. According to the actual situation of recognizing license plate, the ANN (Annual Neural Network) and projecting algorithm are applied to detect and locate the license plate in the video image by using the texture features of the transformed image. The test shows the location accuracy rate for static images is 98%, detection rate of plate is 91%, and processing rate is 0.032 second per frame, which meets the requirements of processing rate in real-time system.

KW - ANN

KW - Characteristic region combination

KW - HSI color model

KW - License diction and plate

UR - https://www.scopus.com/pages/publications/40749124388

M3 - 文章

AN - SCOPUS:40749124388

SN - 0367-6234

VL - 40

SP - 85

EP - 89

JO - Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology

JF - Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology

IS - 1

ER -

An approach to detection and location for license plate based on modified HSI color model

Abstract

Keywords

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