Automatic Water Meter and License Plate Recognition System using Extreme Learning Machine
| Autor: | Hao-Wei Zeng, 曾皓瑋 |
|---|---|
| Rok vydání: | 2017 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 This thesis paper uses Extreme Learning Machines for water meter and license plate recognition, and also uses template matching, Radial Basis Function and Support Vector Machine to compare with Extreme Learning Machines. The most traditional and commonly method is the template matching method, which needs to compare use the template and the input image to compare one by one, and the closest one is result is obtained. The ELM neural network only needs to present the image features. and Put the image features are input to into the neural network then it can get the output result directly, In the output can be directly obtained, and also improve the speed of operation we can effectively. improve the speed of operation in The license plate identification recognition 67 models (new and old license plate), 40 license plate image recognition, the use of template comparison method of operation time is about 3 seconds, The use of ELM is about 0.2 seconds, which is obviously superior to other methods in recognition speed. The recognition rate of EL-ELM is 87.5% and the template comparison method is 70%. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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