• DocumentCode
    2062488
  • Title

    Potholes Detection Based on SVM in the Pavement Distress Image

  • Author

    Lin, Jin ; Liu, Yayu

  • Author_Institution
    Coll. of Math. & Comput. Sci., Fuzhou Univ., Fuzhou, China
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    544
  • Lastpage
    547
  • Abstract
    There are much more researches on the recognition of the cracks on the distress pavement, but the research on the potholes is relatively less. In this paper, Texture measure based on the histogram is extracted as the features of the image region, and the non-linear support vector machine is built up to identify whether a target region is a pothole. Based on this, an algorithm for recognizing the potholes of the pavement is proposed. The experimental results show that the algorithm can achieve a high recognition rate.
  • Keywords
    image recognition; image texture; roads; structural engineering computing; support vector machines; SVM; histogram; image features; image recognition; pavement distress image; potholes detection; support vector machine; Classification algorithms; Feature extraction; Image recognition; Image segmentation; Pixel; Support vector machines; Training; Pavement Potholes; Support Vector Machine (SVM); image recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Distributed Computing and Applications to Business Engineering and Science (DCABES), 2010 Ninth International Symposium on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-7539-1
  • Type

    conf

  • DOI
    10.1109/DCABES.2010.115
  • Filename
    5571563