Automatic Localization of License Plate for Car in Wolfram Mathematica

Author:

Hundzina M. A.1,Zhdanovich M. N.2

Affiliation:

1. Belarusian National Technical University

2. “INTEGRAL” – Management Company of “INTEGRAL” Holding

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.

Publisher

Belarusian National Technical University

Subject

General Medicine

Reference22 articles.

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