KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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An image enhancement Method for extracting multi-license plate region

  • Yun, Jong-Ho (Department of Electronics and Computer Engineering, Hanyang University) ;
  • Choi, Myung-Ryul (Division of Electronics Engineering, Hanyang University) ;
  • Lee, Sang-Sun (Department of Electronics and Computer Engineering, Hanyang University)
  • Received : 2016.10.27
  • Accepted : 2017.03.06
  • Published : 2017.06.30
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Abstract

In this paper, we propose an image enhancement algorithm to improve license plate extraction rate in various environments (Day Street, Night Street, Underground parking lot, etc.). The proposed algorithm is composed of image enhancement algorithm and license plate extraction algorithm. The image enhancement method can improve an image quality of the degraded image, which utilizes a histogram information and overall gray level distribution of an image. The proposed algorithm employs an interpolated probability distribution value (PDV) in order to control a sudden change in image brightness. Probability distribution value can be calculated using cumulative distribution function (CDF) and probability density function (PDF) of the captured image, whose values are achieved by brightness distribution of the captured image. Also, by adjusting the image enhancement factor of each part region based on image pixel information, it provides a function that can adjust the gradation of the image in more details. This processed gray image is converted into a binary image, which fuses narrow breaks and long thin gulfs, eliminates small holes, and fills gaps in the contour by using morphology operations. Then license plate region is detected based on aspect ratio and license plate size of the bound box drawn on connected license plate areas. The images have been captured by using a video camera or a personal image recorder installed in front of the cars. The captured images have included several license plates on multilane roads. Simulation has been executed using OpenCV and MATLAB. The results show that the extraction success rate is more improved than the conventional algorithms.

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References

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