Extraction, Segmentation and Recognition of Vehicle’s License Plate Numbers
In this paper, an automatic vehicle license plate recognition method for Western Australia license plates is proposed. The method consists of three stages, namely, (1) plate extraction; (2) character segmentation; and (3) character recognition. The primary techniques employed in each stage are edge detection, connected component analysis and template matching. An image set of 100 vehicles is generated and used to evaluate the algorithm. The experimental test shows the algorithm’s success rate of 97%, 97% and 98% in Stages 1, 2 and 3, respectively. The respective average time taken in each stage was 234 ms, 37 ms and 29 ms.
KeywordsAutomatic Number Plate Recognition (ANPR) Automatic License Plate Recognition (ALPR) Image analysis Monitoring and surveillance
- 3.Ahmad, I.S., Boufama, B., Habashi, P., Anderson, W., Elamsy, T.: Automatic license plate recognition: a comparative study. In: IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2015), Abu Dhabi, UAE, pp. 635–640 (2015)Google Scholar
- 4.Chen, Y.-T., Chuang, J.-H., Teng, W.-C., Lin, H.-H., Chen, H.T.: Robust license plate detection in nighttime scenes using multiple intensity IP-illuminator. In: IEEE International Symposium on Industrial Electronics (ISIE 2012), Hangzhou, China, pp. 893–898 (2012)Google Scholar
- 7.Zhang, X., et al.: A license plate recognition system based on Tamura texture in complex conditions. In: IEEE International Conference on Information and Automation (ICIA 2010), Harbin, China, pp. 1947–1952 (2010)Google Scholar
- 8.Chen, H., Rivait, D., Gao, Q.: Real-time license plate identification by perceptual shape grouping and tracking. In: IEEE Intelligent Transportation Systems Conference (ITSC 2006), Toronto, Canada, pp. 1352–1357 (2006)Google Scholar