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Volume 44 Issue 6
Jun.  2022
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WANG Dongsheng, WANG Hailong, ZHANG Fang, HAN Linfang, ZHAO Yilin. Infrared Image Defect Information Extraction Based on Temporal Information[J]. Infrared Technology , 2022, 44(6): 565-570.
Citation: WANG Dongsheng, WANG Hailong, ZHANG Fang, HAN Linfang, ZHAO Yilin. Infrared Image Defect Information Extraction Based on Temporal Information[J]. Infrared Technology , 2022, 44(6): 565-570.
shu

Infrared Image Defect Information Extraction Based on Temporal Information

  • 1.

    School of Mechanics and Civil Engineering, China University of Mining & Technology, Beijing 100083, China

  • 2.

    Hebei Key Laboratory of Diagnosis, Reconstruction and Anti-disaster of Civil Engineering, Zhangjiakou 075000, China

  • 3.

    State Key Laboratory for Deep Geomechanics and Underground Engineering, China University of Mining and Technology, Beijing 100083, China

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  • Received Date: July 11, 2021
  • Revised Date: August 21, 2021
    Graphical Abstract
    • Abstract
  • In active infrared thermography technology, the extraction of defect information from infrared images is crucial. Traditional image processing methods can eliminate noise and improve image contrast, but several challenges remain, such as selecting the infrared image manually, subjectivity in the process of infrared image enhancement and segmentation, and information loss in the process of a single infrared image. To overcome these challenges, this study proposes a method for extracting defect information from infrared images based on time sequence information. First, concrete blocks with delamination are fabricated by indoor experiments. Then, active infrared thermal image detection technology is used to collect the infrared image data and temporal information is extracted for each pixel. Finally, the K-means method is used for defect feature extraction based on temporal information. The results show that the defect extraction method based on temporal information can extract hidden defect information. Furthermore, its hierarchical defect information extraction effect is better than that of the K-means method based on the spatial domain.
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    • References (17)
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