JOURNAL OF LIGHT INDUSTRY

CN 41-1437/TS  ISSN 2096-1553

Volume 33 Issue 3
May 2018
Article Contents
LI Liangfu, GAO Xiaoxiao, SUN Ruiyun and et al. Study on bridge floor crack classification method based on sparse coding[J]. Journal of Light Industry, 2018, 33(3): 66-74. doi: 10.3969/j.issn.2096-1553.2018.03.009
Citation: LI Liangfu, GAO Xiaoxiao, SUN Ruiyun and et al. Study on bridge floor crack classification method based on sparse coding[J]. Journal of Light Industry, 2018, 33(3): 66-74. doi: 10.3969/j.issn.2096-1553.2018.03.009 shu

Study on bridge floor crack classification method based on sparse coding

  • Received Date: 2018-03-26
    Available Online: 2018-05-15
  • For the bridge safety and maintenance issues,a sparse coding method for the classification of bridge pavement cracks was proposed.Random downloading of image datasets from the Internet as a training set reduced the amount of manual tagging,and then the camera was used to capture the surrounding bridge crack images as test sets and validation sets.An improved whitening principal component analysis was used to reduce dimensions and accelerate feature learning for these high resolution images.A self-learning algorithm was used to extract scale-invariant features from a large number of unlabeled data sets based on the characteristics of crack images,and an improved sparse code representation was used to obtain a feature dictionary,and the space pyramid was used for pooling.Finally,multiclassification was performed using a linear support vector machine classifier. Experimental results showed that compared with other methods,the proposed algorithm could achieve higher classification accuracy.
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