@article{1584,
  author = {Biao Yang, Qin Yang1, Ruien Kung},
  title = {Two-row License Plate Extraction Based on CIELab Color Space in a Digital Image},
  journal = {Journal of Digital Information Management},
  year = {2014},
  volume = {12},
  number = {5},
  doi = {},
  url = {http://dline.info/fpaper/jdim/v12i5/6.pdf},
  abstract = {A vehicle license plate recognition system
extracts plate information from a digital image through image processing technology. License plate extraction (LPE) is the premise and key concept of license plate recognition systems. In China, two-row license plates are yellow and  dirty. Thus, a novel license plate extraction method based on CIELab color space is
proposed in this paper. The method involves
transforming a digital image from RGB color space to CIELab color space and using the b and a channels of CIELab color space to obtain the yellow areas of the digital image. Morphological operations are implemented to filter out noise and identify the license plate candidate
areas. Lastly, texture features are utilized to locate the real license plate areas. Experiments indicate that the proposed method makes full use of digital image information to rapidly extract two-row license plate areas in a complicated environment. },
}