基于形态学图像处理的车牌自动检测

IF 0.8 Q3 MULTIDISCIPLINARY SCIENCES Malaysian Journal of Fundamental and Applied Sciences Pub Date : 2023-05-26 DOI:10.11113/mjfas.v19n3.2910
Mustafa Qahtan Alsudani, Safa Riyadh Waheed, K. A. Kadhim, M. M. Adnan, Ameer Al-khaykan
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引用次数: 0

摘要

自动车牌识别(ANPR)是计算机视觉最常见的用途之一,也是一个探索得很好的主题,有许多有效的解决方案。然而,由于车牌设计的地区差异,这些解决方案通常针对特定设置进行优化。车牌识别算法往往依赖于这些方面,由于用于开发这些算法的图像分析方法不能保证完美的成功率,因此不可能有一个通用的解决方案。在这项研究中,我们提供了一个专门用于伊拉克全新车牌的算法。该方法采用边缘检测、特征检测和数学形态学对板材进行查找;它是使用OpenCV库在c++中开发的。当在印版上发现字符时,它们被输入Easy OCR引擎进行分析。
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Automatic Car Number Plate Detection using Morphological Image Processing
One of the most common uses of computer vision, automatic number plate recognition (ANPR) is also a pretty well-explored subject with numerous effective solutions. Due to regional differences in license plate design, however, these solutions are often optimized for a specific setting. Number plate recognition algorithms are often dependent on these aspects, making a universal solution unlikely due to the fact that the image analysis methods used to develop these algorithms cannot guarantee a perfect success rate. In this research, we offer an algorithm tailor-made for use with brand-new license plates in Iraq. The method employs edge detection, Feature Detection, and mathematical morphology to find the plate; it was developed in C++ using the OpenCV library. When characters were found on the plate, they were entered into the Easy OCR engine for analysis.
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CiteScore
1.40
自引率
0.00%
发文量
45
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