基于数字图像处理的车牌定位与识别研究(英文)

殷刚; 贾振红; 覃锡忠; 杨杰

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基于数字图像处理的车牌定位与识别研究(英文)

研究精粹 | 更新时间：2026-01-21

- 基于数字图像处理的车牌定位与识别研究(英文)
- 基于数字图像处理的车牌定位与识别研究(英文)
- 新疆大学学报（自然科学版中英文） 2010年27卷第3期页码：258-263
- 作者机构：
  
  1. 新疆大学信息科学与工程学院
  2. 上海交通大学图像处理与模式识别研究所
- 作者简介：
- 基金信息：
  
  Supported by International Cooperation Program of Ministry of Science and Technology of China (No. 2009DFA12870)
- DOI：
  中图分类号： TP391.41
- 纸质出版：2010
- 稿件说明：
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[1]殷刚,贾振红,覃锡忠,等.基于数字图像处理的车牌定位与识别研究(英文)[J].新疆大学学报(自然科学版),2010,27(03):258-263.

殷刚, 贾振红, 覃锡忠, et al. 基于数字图像处理的车牌定位与识别研究(英文)[J]. Journal of Xinjiang University (Natural Science Edition in Chinese and English), 2010, 27(3): 258-263.
[1]殷刚,贾振红,覃锡忠,等.基于数字图像处理的车牌定位与识别研究(英文)[J].新疆大学学报(自然科学版),2010,27(03):258-263. DOI：

殷刚, 贾振红, 覃锡忠, et al. 基于数字图像处理的车牌定位与识别研究(英文)[J]. Journal of Xinjiang University (Natural Science Edition in Chinese and English), 2010, 27(3): 258-263. DOI：

摘要

研究了车牌图像的特征

车牌定位算法基于车牌图像颜色特征

选取适合的颜色模型进行车牌提取

将彩色车牌图像转化为灰度图像.采用基于矩的阈值选取方法进行图像二值化处理

Hough变换的方法对图像进行倾斜校正

最后对已预处理增强的图像进行Sobel垂直算子边缘检测

用阈值分割出前景

搜索出符合车牌字符特征的候选区域

对候选区域进一步分析得到牌照位置.提出并采用基于PCA-BP神经网络的字符识别算法对车牌进行识别

300ms内车牌字符识别率达97.5%

实验证明

在训练样本较少的情况下

该系统的识别率依然较高.

Abstract

The license plate image features is studied

the appropriate color model for license plate extraction is selected

the color plate images are converted to gray image

a method based on moment threshold selection is used to create the binary image.Hough transform is used to resolve the problem of Skew Correction

it detected the pre-processed and enhanced image with Sobel vertical operators

the foreground of the image is segmented with threshold.Through the analysis of the projection figure and rectangle transformation

the possible regions of the license plate are found.A recognition algorithm for vehicle-license-plate characters based on PCA-BP neural network is presented and adopted in this paper for license plate character recognition in complex background

this algorithm has high speed and accuracy

license plate character recognition rate reach 97.5% within 300 ms

experiments show that even in the case of small training samples

the system recognition rate is still high.

关键词

Keywords

references

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