Recognition of speed signs in uncertain and dynamic environments

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dc.contributor.authorZhu, Zhilong
dc.contributor.authorXu, Gang
dc.contributor.authorHe, Hongmei
dc.contributor.authorJiang, Juanjuan
dc.contributor.authorWang, Tao
dc.date.accessioned2020-04-01T15:35:53Z
dc.date.available2020-04-01T15:35:53Z
dc.date.issued2019-05-08
dc.description.abstractThe speed limit signs recognition directly affects the safety of autonomous vehicles. Vehicles are usually running in an uncertain and dynamic environment. The performance of the recognition system is affected by various factors such as the different sizes of pictures, illumination condition and position circumstances, which can lead to misclassification. This makes the speed sign recognition challengeable. To improve the recognition rate of the speed signs in such environments, this work firstly applies the method of the saliency target detection based on the background-absorbing Markov chain, to extract the node in an image, then uses SPP-CNN to classify the extracted nodes with ten-folder validation. The recognition rate is up to 9.32%, higher than that obtained directly by SPP-CNN working on raw dataset.en_UK
dc.identifier.citationZhu Z, Xu G, He H, et al., (2019) Recognition of speed signs in uncertain and dynamic environments. Journal of Physics: Conference Series, Volume 1187, Issue 4, 2019, Article Number 042066en_UK
dc.identifier.issn1742-6588
dc.identifier.urihttps://doi.org/10.1088/1742-6596/1187/4/042066
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/15357
dc.language.isoenen_UK
dc.publisherIOP Publishing: Conference Seriesen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleRecognition of speed signs in uncertain and dynamic environmentsen_UK
dc.typeArticleen_UK

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