Identifying blurry car license number plate using machine learning

Erika Sawada; Ayaka Fujima; Seiichi Gohshi; Naiwala P. Chandrasiri

doi:10.1117/12.2566798

1 June 2020 Identifying blurry car license number plate using machine learning

Erika Sawada, Ayaka Fujima, Seiichi Gohshi, Naiwala P. Chandrasiri

Proceedings Volume 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020; 115150P (2020) https://doi.org/10.1117/12.2566798
Event: International Workshop on Advanced Imaging Technologies 2020 (IWAIT 2020), 2020, Yogyakarta, Indonesia

Abstract

Equipment used in a crime is a clue to solve cases. Cars are often used in crimes for transportation. Security cameras are set in everywhere of downtowns. Drive recorders are set in many cars in Japan. Security cameras and drive recorders can record an image of a license number plate. However, the license number plate is often recorded in a small part of the image. It is needed to enlarge the image to read. However, the enlarged image is in low-resolution and blurry. Therefore, edges of the image are not clear. It is difficult to read the number plate from the low-resolution and blurry image. Machine learning has been used to identify blurry letters in an image. Performances of machine learning method change depending on classifiers. In this paper, performances of five classifiers for identifying the license number plate were compared. The proposed research can potentially contribute in solving criminal cases.

Citation Download Citation

Erika Sawada, Ayaka Fujima, Seiichi Gohshi, and Naiwala P. Chandrasiri "Identifying blurry car license number plate using machine learning", Proc. SPIE 11515, International Workshop on Advanced Imaging Technology (IWAIT) 2020, 115150P (1 June 2020); https://doi.org/10.1117/12.2566798

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KEYWORDS

Machine learning

Feature extraction

Binary data

Image processing

Cameras

Information science

Gaussian filters

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