| Autor: |
Mohamed Chouai, José-Luis Sancho-Gómez, Malika Mimi, Mostefa Merah |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Advances in Science, Technology & Innovation ISBN: 9783030534394 |
| DOI: |
10.1007/978-3-030-53440-0_11 |
| Popis: |
Aviation security screening systems have been considerably strengthened since the attacks of September 11, 2001. To date, almost all used baggage control systems are managed manually by human operators. The latter remains essential in this type of technology; however, it presents a number of risk factors such as distraction or errors of inattention, which constitutes a major risk. Therefore, the need for intelligent transportation systems is convenient. This paper presents an automatic color-based segmentation for object detection in X-ray baggage images at airports. It is based on the use of machine learning to perform the color-based segmentation of X-ray images of scanned baggage. A comparative study between eight different machine learning methods is carried out with the optimization of the hyperparameters for a better design of the different models. The results obtained over our private database (High Tech Detection Systems HDTS) composed by dual-energy X-ray luggage scan images showed a perfect object detection without practically any false detection. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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