ACS Applied Computer Science

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The purpose of this paper is to design and implement an automatic number plate recognition system. The system has still images as the input, and extracts a string corresponding to the plate number, which is used to obtain the output user data from a suitable database. The system extracts data from a license plate and automatically reads it with no prior assumption of background made. License plate extraction is based on plate features, such as texture, and all characters segmented from the plate are passed individually to a character recognition stage for reading. The string output is then used to query a relational database to obtain the desired user data. This particular paper utilizes the intersection of a hat filtered image and a texture mask as the means of locating the number plate within the image. The accuracy of location of the number plate with an image set of 100 images is 68%.

  • APA 6th style
Abdulhamid, M., & Kinyua, N. (2020). Software for recognition of car number plate. Applied Computer Science, 16(1), 73-84. doi:10.23743/acs-2020-06
  • Chicago style
Abdulhamid, Mohanad, and Njagi Kinyua. "Software for Recognition of Car Number Plate." Applied Computer Science 16, no. 1 (2020): 73-84.
  • IEEE style
M. Abdulhamid and N. Kinyua, "Software for recognition of car number plate," Applied Computer Science, vol. 16, no. 1, pp. 73-84, 2020, doi: 10.23743/acs-2020-06.
  • Vancouver style
Abdulhamid M, Kinyua N. Software for recognition of car number plate. Applied Computer Science. 2020;16(1):73-84.