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
Full text of article: Russian language.
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.
hierarchical temporal memory, temporal grouping, license plate detection.
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