Automatic Localization of License Plate for Car in Wolfram Mathematica

M. Hundzina, M. N. Zhdanovich
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Abstract

Modern imaging devices make it possible to solve a complex of technical applied problems that require the synthesis and analysis of computer processing methods using threshold binarization, image classification, clustering, and the use of machine  learning to determine  areas of interest.  Thus,  segmentation  algorithms are widely  used for processing  medical  images. Computer technologies are used for the functioning of the intellectual environment, which allows to analyze the state of human health. The development of microelectronics makes it possible to increase the complexity of the applied image processing algorithms used to solve applied engineering problems. The issues of segmentation, pattern recognition, description and presentation of details, morphological analysis of images obtained by industrial equipment are widely discussed in the literature. For example, theories of optical signal processing taking into account interference, issues of image perception and analysis are presented in detail in domestic and foreign literature. The paper describes the  developed algorithm for localizing a car license plate, implemented in the Wolfram Mathematica system. First, the region of interest is determined, isolated from the rest of the image for its subsequent processing. An image representation is implemented using an affine transformation. Further segmentation of the characters on the license plate allows the characters to be identified. In the Mathematica system, a program code for the car license plate localization  algorithm  for its further recognition  has been  developed. The solution to the problem was obtained using the step-by-step application of the built-in and user-defined functions of the Wolfram Mathematica system. The algorithm has been tested on a representative sample of images. The average error did not exceed 10 %, which is in line with modern industrial image processing algorithms. The resulting car license plate identification algorithm can be used in digital devices to automatically determine and further image processing.
Wolfram Mathematica中汽车车牌的自动定位
现代成像设备使解决复杂的技术应用问题成为可能,这些问题需要使用阈值二值化,图像分类,聚类和使用机器学习来确定感兴趣的领域的计算机处理方法的综合和分析。因此,分割算法被广泛应用于医学图像的处理。计算机技术被用于智能环境的功能,它允许分析人类健康状况。微电子技术的发展使得用于解决应用工程问题的应用图像处理算法的复杂性增加成为可能。对工业设备获得的图像进行分割、模式识别、细节的描述和呈现、形态分析等问题在文献中得到了广泛的讨论。例如,国内外文献详细介绍了考虑干扰的光信号处理理论、图像感知和分析问题。本文介绍了在Wolfram Mathematica系统中实现的车牌定位算法。首先,确定感兴趣的区域,将其与图像的其余部分隔离,以便进行后续处理。使用仿射变换实现图像表示。进一步分割车牌上的字符可以识别字符。在Mathematica系统中,为进一步识别车牌,开发了车牌定位算法的程序代码。通过逐步应用Wolfram Mathematica系统的内置函数和用户自定义函数,得到了问题的解决方案。该算法已在具有代表性的图像样本上进行了测试。平均误差不超过10%,符合现代工业图像处理算法的要求。所得到的汽车车牌识别算法可用于数字设备的自动确定和进一步的图像处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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