Detection of fonts and characters with hybrid graphic-text plate numbers
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 pl...
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Main Authors: | , , , |
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Format: | text |
Published: |
Animo Repository
2019
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Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2599 |
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Institution: | De La Salle University |
Summary: | 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. |
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