Abstract
Managing parking lots usually involve tasks that should provide important information such as parked car counts, and available parking spaces and their locations. This can be used to direct drivers in real-time towards empty spaces which will minimise the time spent looking for one and thus reduce traffic congestions. Using an image-based integrated parking system is an effective way to automatically track a parking lot without exhausting time and manual resources. In this paper, we present a low-cost vision-based parking system to manage a closed area parking lot by using cameras that takes real-time footage of the parking lot. The footage is processed using HSV-based histogram technique and the resulting models are compared against pre-trained models. These models define either a Parked or an Empty class. The parking spaces within the processed footage are then categorised using this two classes based on their matching probability.
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Ahmad, A., Phon-Amnuaisuk, S. (2016). Low Cost Parking Space Management System. In: Lavangnananda, K., Phon-Amnuaisuk, S., Engchuan, W., Chan, J. (eds) Intelligent and Evolutionary Systems. Proceedings in Adaptation, Learning and Optimization, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-27000-5_31
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DOI: https://doi.org/10.1007/978-3-319-27000-5_31
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