Thai Traffic Sign Classification and Recognition System Based on Histogram of Gradients, Color Layout Descriptor, and Normalized Correlation Coefficient
| Autor: | Suphakant Phimoltares, Nattapol Namyang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry Template matching Feature extraction 020206 networking & telecommunications Pattern recognition 02 engineering and technology Random forest Support vector machine ComputingMethodologies_PATTERNRECOGNITION Histogram of oriented gradients Categorization Histogram Color layout descriptor 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Sign (mathematics) |
| Zdroj: | 2020 - 5th International Conference on Information Technology (InCIT). |
| DOI: | 10.1109/incit50588.2020.9310778 |
| Popis: | The traffic sign is one of the useful features for improving driving assistance technology. There are some different patterns in each country. As a result, this paper proposes the classification and recognition system, which are applicable to the Thai traffic sign. In the classification process, two classifiers: support vector machine (SVM) and random forest are combined and run on two selected features: histogram of oriented gradients (HOG) and color layout descriptor (CLD) to categorize an incoming sign into one of four classes. In this process, the proposed technique provides the accuracy score up to 93.98%. Subsequently, the recognition process is used to identify each traffic sign. This process is based on the OCR and correlation coefficient-based template matching. From the experiments, our proposed system can be applied to a sign image and used as a part of driving assistance system. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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