A novel license plate recognition method based on least squares support vector machine

Lin Gui

doi:10.1117/12.920246

13 January 2012 A novel license plate recognition method based on least squares support vector machine

Lin Gui

Proceedings Volume 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies; 83501L (2012) https://doi.org/10.1117/12.920246
Event: Fourth International Conference on Machine Vision (ICMV 11), 2011, Singapore, Singapore

Abstract

Support vector machine (SVM) is a new type of machine learning method based on statistical learning. It avoids the neural network of some inherent disadvantages, such as the local minimum in the training process, structure, selection, slow convergence speed problem, have very strong nonlinear system identification and generalization ability and small sample. In this paper, we established multi-classifier based on binary tree model. Category rules are based on experience. But this method cans classifier to come to less than optimal results. Our future work focused on how to find a category to get the optimal rules of multi-classifier method, experience risk analysis, cluster analysis will consider further.

Citation Download Citation

Lin Gui "A novel license plate recognition method based on least squares support vector machine", Proc. SPIE 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies, 83501L (13 January 2012); https://doi.org/10.1117/12.920246

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KEYWORDS

Wavelets

Image segmentation

Neural networks

Image processing

Optical character recognition

Binary data

Computing systems

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