First Asia International Conference on Modelling & Simulation (AMS'07) Comparison of Feature Extractors in License Plate Recognition Prince of Songkla University, Phuket, Thailand March 27-March 30 ISBN: 0-7695-2845-7
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AMS.2007.25
Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. In this paper, an automatic license plate recognition system is proposed for Malaysian vehicles with standard license plates using blob labeling and clustering for segmentation, seven popular and one proposed edge detectors for feature extraction and neural networks for classification.There were eight experiments conducted using eight different edge dectectors: Kirsch, Sobel, Laplacian, Wallis, Prewitt, Frei Chen and a proposed edge detector. The result had shown kirsch edge detectors is the best technique for feature exractor while the proposed achieved better results compared to Prewitt, Frei Chen and Wallis.
Citation:
Siti Norul Huda Sheikh Abdullah, Marzuki Khalid, Rubiyah Yusof, Khairuddin Omar, "Comparison of Feature Extractors in License Plate Recognition," ams, pp.502-506, First Asia International Conference on Modelling & Simulation (AMS'07), 2007 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||