License plate localization based on Kapur optimal multilevel threshold
| Autor: | Azizi Abdullah, Mohd Zamri Murah, Abbas Salimi Zaini, Siti Norul Huda Sheikh Abdullah, Shariffpudin Basiron, Nur Aliyatul Husna Bt Yahya |
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| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science 020206 networking & telecommunications 02 engineering and technology Image segmentation Thresholding 0202 electrical engineering electronic engineering information engineering Entropy (information theory) 020201 artificial intelligence & image processing Computer vision Segmentation Artificial intelligence business License |
| Zdroj: | 2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence. |
| Popis: | A license plate localization system is useful for many applications. Due to ambient of lighting in three distinct situation which are morning, afternoon and night causing difficulty to search optimum threshold value in each situation. This research uses global thresholding approach by using Kapur entropy multilevel threshold based on Patch-Levy Bees Algorithm (PLBA). As a result, the system properly localize and identify number plate in the image by using proposed segmentation image. From the experiment, proposed method are achieve accuracy rates to 67.68%, 90.71%, 24.34% respectively for morning, afternoon and night dataset. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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