Publication: Vehicle detection on a pint-sized computer
Issued Date
2017-03-23
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2-s2.0-85017509156
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Mahidol University
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SCOPUS
Bibliographic Citation
2017 9th International Conference on Knowledge and Smart Technology: Crunching Information of Everything, KST 2017. (2017), 40-44
Suggested Citation
Thanida Tangkocharoen, Ananta Srisuphab Vehicle detection on a pint-sized computer. 2017 9th International Conference on Knowledge and Smart Technology: Crunching Information of Everything, KST 2017. (2017), 40-44. doi:10.1109/KST.2017.7886078 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/42376
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Vehicle detection on a pint-sized computer
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Abstract
© 2017 IEEE. Powerful miniature single-board computers have recently gained attention, inviting computer scientists and engineers to develop various kinds of applications on these tiny devices. Having numerous benefits over full-scaled personal computers, their small size enables system mobility and allows operations under limited power resources. Exploring its computing capability, we set up a Raspberry Pi with a high-resolution camera. Its task is to detect vehicles based on image processing techniques. This is generally regarded as a computationally demanding process. Our system implements Haar-like features and a supervised cascade learning model. Empirical results are impressive, achieving good detection rate with an average sustained image rate of 2 Hz.