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Volume 45 Issue 11
Nov.  2023
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ZHOU Dengke, GUO Xingchen, SHI Kaite, TANG Peng, ZHENG Kaiyuan, MA Pengge. Infrared Blade Image Stitching Algorithm for Wind Farm UAV Inspection[J]. Infrared Technology , 2023, 45(11): 1161-1168.
Citation: ZHOU Dengke, GUO Xingchen, SHI Kaite, TANG Peng, ZHENG Kaiyuan, MA Pengge. Infrared Blade Image Stitching Algorithm for Wind Farm UAV Inspection[J]. Infrared Technology , 2023, 45(11): 1161-1168.
shu

Infrared Blade Image Stitching Algorithm for Wind Farm UAV Inspection

  • 1.

    China Three Gorges Corporation Research Institute, Beijing 100038, China

  • 2.

    Zhengzhou University of Aeronautics, Zhengzhou 450015, China

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  • Received Date: September 25, 2022
  • Revised Date: December 12, 2022
    Graphical Abstract
    • Abstract
  • Aiming at more redundant background information and low stitching accuracy of the infrared images of the blades taken by UAV (Unmanned Aerial Vehicle), In this study, we proposed a stitching algorithm for infrared wind turbine blade images combining the Chan-Vese model and morphology. First, we subjected the image to median filtering and noise reduction, and a morphological operation improved a level-set algorithm based on the Chan-Vese model to generate the mask of the expression subject. We extracted Harris feature points by removing redundant backgrounds based on the mask. We performed morphological etching on the mask to suppress the pseudo-feature points on the boundary-jagged pixels. We used violent matching and the RANSAC algorithm to screen out effective matching point pairs and calculate the homography matrix to realize matching and splicing. Compared with the Harris stitching algorithm under traditional image segmentation, the stitching accuracy of the improved algorithm significantly improved, and it showed strong robustness in different test scenarios.
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    • References (14)
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