Detection of fonts and characters with hybrid graphic-text plate numbers

• Main Authors: Brillantes, Allysa Kate M., Bandala, Argel A., Dadios, Elmer Jose P., Jose, John Anthony C.
• Format: text
• Published: Animo Repository 2019
• Subjects: Optical character recognition; Automobile license plates; Template matching (Digital image processing); Electrical and Computer Engineering; Electrical and Electronics; Systems and Communications
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2599
• Institution: De La Salle University

Philippine license plates have different plate styles and character fonts making the plate character recognition challenging. This paper focuses on improving the segmentation method to recognize characters of different formats of Philippine license plates. The proposed system comprises of license plate classification, character segmentation and character recognition. License plate series was classified using color level of pixels in the image. Plate characters were segmented using 3-Class Fuzzy Clustering with Thresholding and Connected Component Analysis and were recognized using Template Matching. The system achieved an accuracy of 95% and 70% for the 2003 plate series and 2014 plate series, respectively, having tested 20 license plates from each series. © 2018 IEEE.