Fuzzy adaptive pre-processing models for road sign recognition

Chien Chuan Lin, Ming-Shi Wang, Tang Chun Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We proposed fuzzy inference schemes to address the changes of the lighting environment problems: the illumination of the images captured from camera installed on a moving vehicle also varies from frame to frame. First, the input image is checked with a fuzzy inference method to evaluate the illumination conditions in order to apply appropriate preprocessing operations to get a better result. To overcome the effects caused by vehicle speed and changes in direction, a fuzzy inference method was again used to select an adapted detection window to increase the throughput rate. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the detected road sign. The mandatory and warning road traffic signs are the processing targets in this research. The proposed system can detect and recognize road signs correctly from the captured image, and not only overcome problems such as low illumination, viewpoint rotation, partial occlusion and rich red color around the road sign, but also reach a high recognition rate and processing performance.

Original languageEnglish
Title of host publicationProceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010
Pages642-647
Number of pages6
DOIs
Publication statusPublished - 2010 Dec 1
Event2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010 - Kitakyushu, Japan
Duration: 2010 Dec 152010 Dec 17

Publication series

NameProceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010

Other

Other2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010
CountryJapan
CityKitakyushu
Period10-12-1510-12-17

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science

Fingerprint Dive into the research topics of 'Fuzzy adaptive pre-processing models for road sign recognition'. Together they form a unique fingerprint.

  • Cite this

    Lin, C. C., Wang, M-S., & Yang, T. C. (2010). Fuzzy adaptive pre-processing models for road sign recognition. In Proceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010 (pp. 642-647). [5716295] (Proceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010). https://doi.org/10.1109/NABIC.2010.5716295