License plate recognition algorithm on the basis of a connected components method and a hierarchical temporal memory model
Yu.A. Bolotova, V.G. Spitsyn, M.N. Rudometkina

 

Tomsk Polytechnic University

 

DOI: 10.18287/0134-2452-2015-39-2-275-280

Full text of article: Russian language.

Abstract:
This paper proposes a license plate recognition algorithm that consists of three major steps: image preprocessing, segmentation, and recognition, which works efficiently with day- and nighttime images, as well as with the license plate being tilted.
Pre-filtration allows the sequential binarization to be conducted efficiently. Typically, the license plate segmentation is realized by a histogram method with the preliminary plate de-rotation to the horizontal position, thus deteriorating the original image quality. In this paper the segmentation is implemented by a connected components method, enabling the rotation and a consequent loss of quality to be avoided. The hierarchical temporal network shows good results in rotated symbols recognition. The proposed method can be used in a similar way for segmentation and recognition of various text data. The proposed algorithms can also be used for distorted text segmentation and recognition.

Keywords:
hierarchical temporal memory, temporal grouping, license plate detection.

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