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Intelligent Detection Method of Defects in High-Rise Building Facades Using Infrared Thermography.

Daiming Liu1, Yongqiang Jin2, Yuan Yang2

  • 1School of Mechanical Engineering, Sichuan University, Chengdu 610065, China.

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|January 28, 2026
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Summary
This summary is machine-generated.

This study introduces an intelligent method for detecting high-rise building facade defects using infrared imaging. The approach enhances accuracy by refining image segmentation and employing advanced object detection, improving inspection reliability.

Keywords:
DeepLabV3+YOLOV11defect detectionsemantic segmentation

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Area of Science:

  • Building Engineering
  • Computer Vision
  • Materials Science

Background:

  • High-rise building facades are susceptible to defects from environmental exposure.
  • Infrared thermography for facade inspection faces challenges with low accuracy due to interference and blurred boundaries.

Purpose of the Study:

  • To develop an intelligent, accurate defect detection method for high-rise building facades using infrared images.
  • To overcome limitations of traditional infrared inspection methods, including interference and blurred defect edges.

Main Methods:

  • A two-stage approach: DeepLabV3+ segmentation with a novel boundary refinement module and triple constraint loss for interference removal.
  • YOLOv11 object detection model applied to segmented images for identifying specific defects like cracks and detachments.
  • Superpixel Linear Iterative Clustering (SLIC) for enhanced prediction smoothness and robustness.

Main Results:

  • Achieved 89.7% detection precision and 87.9% mAP@0.5 on a dataset of 180 UAV-collected infrared images.
  • Demonstrated superior performance compared to existing algorithms in identifying facade defects.
  • Successfully mitigated issues of interferences and blurred boundaries in infrared facade inspection.

Conclusions:

  • The proposed intelligent defect detection method significantly improves the accuracy and reliability of high-rise building facade inspections.
  • The combination of advanced segmentation and detection models offers a robust solution for complex infrared imaging challenges.
  • This method provides a valuable tool for proactive building maintenance and safety.