Restoration of Motion-Blurred Image Based on Border Deformation Detection: A Traffic Sign Restoration Model

PLoS One. 2015 Apr 7;10(4):e0120885. doi: 10.1371/journal.pone.0120885. eCollection 2015.


Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Automobile Driving*
  • Humans
  • Image Interpretation, Computer-Assisted / instrumentation*
  • Location Directories and Signs
  • Models, Theoretical*
  • Motion
  • Pattern Recognition, Automated / methods*

Grant support

This work was supported by the National Natural Science Foundation of China (Grant No. 61174181), the Advanced Research Fund (Grant No. 9140A05030214QT02070), and the National Basic Research Program of China (973 Program, Project No. 2012CB725405). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.