Vol. 2, Issue 1, January 2020, pp. 10 - 23 Ibiyemi, Owotogbe & Adu (2020). A Comparative Study of Vehicle Number Plate Recognition Systems © 2020 Afr. J. MIS. https://afrjmis.net A Comparative Study of Vehicle Number Plate Recognition Systems T. S. Ibiyemi 1 , J. S. Owotogbe 2 and B. A. Adu 3 1 Vice Chancellor’s Office, 2-3 Dept. of Mathematical Sciences, Achievers University, Owo, Nigeria. Email: 1 ibiyemits@yahoo.com, 2 owotogbesegunjoshua@gmail.com, 3 adubosede2@gmail.com ABSTRACT The traffic management based on vehicle number plate recognition in Nigeria has not recorded the much expected result because it is manually done. Having studied the existing solution, it is opined that every nation has its unique vehicle number plate, and off – the – shelf automatic number plate recognition system developed for one nation is not likely to work optimally for another nation. Despite the fact that the new Nigerian number plate system was announced in 2011, it is observed that quite a large number of vehicles on Nigerian roads still have the old number plate system. However, the system that will detect and recognize both Nigerian number plate systems has not been announced. Hence, the need to develop a system to detect and recognize both Nigerian number plate systems. Therefore, the aim of this paper is to carry out a comparative study of existing vehicle number plate recognition systems, especially for Nigerian roads and also to carry out experimental studies on Nigerian number plate recognition systems. The methodology used includes the acquisition of 934 sample images of new Nigerian number plates and 567 sample images of old Nigerian number plates. Then pre- processing of the acquired images, extraction of the identification on the number plate via character segmentation, character normalization (extracted characters reduced to 42 x 24 pixels), feature extraction and recognition of the extracted characters using template matching. From the study and analysis of the test, individual character recognition accuracy of 86% was gotten from the dataset, which shows that 791 sample images of new Nigerian number plates and 499 old Nigerian number plates were successfully recognized. Due to the errors encountered during implementation, it is recommended to create new character template with the same font as that on Nigerian number plate for accuracy. Keywords: Template matching, Number plate recognition system, Preprocessing, Optical Character Recognition. ___________________________________________ Reference Format: Ibiyemi, T. S., Owotogbe, J. S., and Adu, B. A. (2020), A Comparative Study of Vehicle Number Plate Recognition Systems, Afr. J. MIS, Vol. 2, Issue 1, pp. 10 - 23. © Afr. J. MIS, January 2020. 1