License Plate Recognition Algorithm on the basis of a Connected Components method and a Hierarchical Temporal Memory Model

Y. U. Bolotova, V. G. Spitsyn, M. N. Rudometkina

Research output: Contribution to journalArticle

6 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)275-280
Number of pages6
JournalComputer Optics
Issue number2
Publication statusPublished - 1 Apr 2015



  • Hierarchical temporal memory
  • License plate detection
  • Temporal grouping

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Computer Science Applications
  • Electrical and Electronic Engineering

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