Image perception hash and structural similarity fusion model for parking lot status recognition
In order to improve the recognition accuracy of parking space change, a new fusion model is proposed. The image-aware hash technique and image structure similarity algorithm are combined to construct a new parking space state combination discriminating index due to the accuracy of the recognition. T...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Taylor & Francis Group
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/ad5ccf0b0b4b437385e8857baa7847db |
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| Sumario: | In order to improve the recognition accuracy of parking space change, a new fusion model is proposed. The image-aware hash technique and image structure similarity algorithm are combined to construct a new parking space state combination discriminating index due to the accuracy of the recognition. Time is used to define the discriminating threshold of the parking space occupancy condition, so as to construct a vehicle position state discriminating fusion model. Based on the model, the parking lot recognition software was developed, and the parking space recognition of three environmental states, such as uniform illumination, uneven illumination and snowfall, was carried out and the validity of the model was verified. |
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