Detection of Direction Indicators on Road Surfaces Using Inverse Perspective Mapping and NN


KIPS Transactions on Software and Data Engineering, Vol. 4, No. 4, pp. 201-208, Apr. 2015
10.3745/KTSDE.2015.4.4.201, Full Text:

Abstract

This paper proposes a method for detecting the direction indicator shown in the road surface efficiently from the black box system installed on the vehicle. In the proposed method, the direction indicators are detected by inverse perspective mapping(IPM) and bag of visual features(BOF)-based NN classifier. In order to apply the proposed method to real-time environments, the candidated regions of direction indicator in an image only performs IPM, and BOF-based NN is used for the classification of feature information from direction indicators. The results of applying the proposed method to the road surface direction indicators detection and recognition, the detection accuracy was presented at least about 89%, and the method presents a relatively high detection rate in the various road conditions. Thus it can be seen that the proposed method is applied to safe driving support systems available.


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Cite this article
[IEEE Style]
J. B. Kim, "Detection of Direction Indicators on Road Surfaces Using Inverse Perspective Mapping and NN," KIPS Transactions on Software and Data Engineering, vol. 4, no. 4, pp. 201-208, 2015. DOI: 10.3745/KTSDE.2015.4.4.201.

[ACM Style]
Jong Bae Kim. 2015. Detection of Direction Indicators on Road Surfaces Using Inverse Perspective Mapping and NN. KIPS Transactions on Software and Data Engineering, 4, 4, (2015), 201-208. DOI: 10.3745/KTSDE.2015.4.4.201.