Occlusion-robust Traffic Sign Detection via Cascaded Colour Cubic Feature

The high variability of sign appearance with partial occlusions in uncontrolled environments has made the detection of traffic signs a challenging problem in computer vision. In this study, an occlusion-robust traffic sign detection framework is proposed. To achieve occlusion-robust detection, a colour cubic feature called colour cubic local binary pattern (CC-LBP) is proposed to construct a coarse-to-fine cascaded detector. The CC-LBP utilises colour information and a self-adaptive threshold to express multiclass traffic signs, which can effectively remove non-object subwindows in the cascade-based detection. The verification experiments show that the proposed CC-LBP feature performs better than the previous rectangular features in representing multiclass traffic signs, and that the proposed occlusion-robust detection method can detect multiclass partial occluded traffic signs with high accuracy in real time.

Record URL:
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/1751956X
Supplemental Notes:
- Abstract reprinted with permission of the Institution of Engineering and Technology.
Authors:
- Liu, Chunsheng
- Chang, Faliang
- Liu, Chenyun
Publication Date: 2016-6

Language

English

Media Info

Media Type: Web
Features: References;
Pagination: pp 354-360
Serial:
- IET Intelligent Transport Systems
- Volume: 10
- Issue Number: 5
- Publisher: Institution of Engineering and Technology (IET)
- ISSN: 1751-956X
- EISSN: 1751-9578
- Serial URL: https://ietresearch.onlinelibrary.wiley.com/journal/17519578
Publication flags:
Open Access (libre)

Subject/Index Terms

TRT Terms: Accuracy; Color; Computer vision; Detection and identification systems; Image analysis; Traffic signs
Subject Areas: Data and Information Technology; Highways;

Filing Info

Accession Number: 01602762
Record Type: Publication
Files: TRIS
Created Date: Jun 21 2016 4:10PM