Earticle

초록

영어

In this paper, the methods of correcting skew vehicle license plate and segmenting characters in plate are discussed first. An approach making use of self-organizing map (SOM) is introduced to find the tilt angle of plate which simultaneously educes seven important points with coordinates being elements of weight matrix. After necessary processing to corrected plate, a character segmentation algorithm based on the shortest distance classification is presented, which takes advantage of exactly seven points gained from SOM as class centers. In the next place, a hybrid algorithm cascading two steps of template matching is utilized to recognize Chinese characters segmented from the license plates, which is based on the connected region feature and standard deviation feature extracted from sample corresponding to each template. Experimental results show that the proposed method can be implemented efficiently.

목차

Abstract
 1. Introduction
 2. Slant Correction of License Plate
  2.1. A brief introduction of SOM
  2.2. Skew Plate Correction Approach based on SOM
  2.3. Slant correction experiment
 3. Segmentation of Characters in Plate
  3.1. Preparation
  3.2. Character Segmentation
 4. Chinese Character Recognition
  4.1. Connected Domains in Binary Image
  4.2. Feature Extraction based on Templates
  4.3. The Approach of Character Recognition
  4.4. Experimental Results
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Rong Cheng [ School of Science, North University of China, China School of Information and communication Engineering, North University of China, China ]
• Yanping Bai [ School of Science, North University of China, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605