Control Systems and Computers, N6, 2017, Article 3

DOI: https://doi.org/10.15407/usim.2017.06.026

Upr. sist. maš., 2017, Issue 6 (272), pp. 26-34, 40.

UDC 004.89:004.93

Volodymyr M. Kyyko  PhD in Techn. Sciences, senior researcher of pattern recognition departmation, International Research and Training Centre of Information Technologies and Systems of the NAS and MES of Ukraine, Glushkov ave., 40, Kyiv, 03187, Ukraine, vkiiko@gmail.com

License Plate Localization and Recognition in Images  

Introduction. The well known algorithms and systems for license plate localization and recognition are observed. Some ways for increasing robustness of recognition are defined.
Purpose. It is important to provide robust license plates recognition under conditions of long-distance and not frontal location of camera relatively to license plate. To reduce processing time it is desired also preliminary to detect a small number of image parts which may contain license plates and precisely localize these plates.

Methods. Localization of number plates is based on detection of license plate frame contour lines by Hough transform. While recognition special points in symbol contour are detected    and modified Levenstein distances are computed between input and etalon chains of these points. Separation of similar in shape symbols is carried out by detection of additional structural and metrical contour features. Used structural and metrical features of symbols are robust in a great measure to scaling and rotations of symbols in image.

Results. The results of experimental testing of the proposed localization and recognition algorithms are presented. Conclusion. Proposed algorithms can be used as basis for new as well as in developed before systems for license plates recognition in images. 

Keywords: images, license plates localization and recognition, Levenstein distance, Hough transform.

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Received 04.10.2017