职玉, 朱娟娟, 刘锐, 张海东. 应用特征轮廓四边形的热红外图与可见光图配准[J]. 红外与激光工程, 2021, 50(S2): 20200520. DOI: 10.3788/IRLA20200520
引用本文: 职玉, 朱娟娟, 刘锐, 张海东. 应用特征轮廓四边形的热红外图与可见光图配准[J]. 红外与激光工程, 2021, 50(S2): 20200520. DOI: 10.3788/IRLA20200520
Zhi Yu, Zhu Juanjuan, Liu Rui, Zhang Haidong. Registration of thermal infrared image and visible image based on featured contour quadrilateral[J]. Infrared and Laser Engineering, 2021, 50(S2): 20200520. DOI: 10.3788/IRLA20200520
Citation: Zhi Yu, Zhu Juanjuan, Liu Rui, Zhang Haidong. Registration of thermal infrared image and visible image based on featured contour quadrilateral[J]. Infrared and Laser Engineering, 2021, 50(S2): 20200520. DOI: 10.3788/IRLA20200520

应用特征轮廓四边形的热红外图与可见光图配准

Registration of thermal infrared image and visible image based on featured contour quadrilateral

  • 摘要: 热红外图与可见光图的融合分析在智能安防和故障检测中应用广泛。针对同一场景下两图像在融合过程中难以匹配的问题,提出了一种基于特征轮廓四边形的图像配准方法。首先通过分割算法分别对热红外图和可见光图进行过滤;再进行边缘轮廓点的检测和轮廓的重新绘制;然后通过算法筛选出特征轮廓并进行多边形近似,生成特征轮廓的外接四边形;将此四边形顶点代入改进的单应性变换模型计算参数,其中加入了位移变量偏差值可中和80%的误差;最后,通过单应性变换模型对热红外图进行变换配准。实验结果表明,该方法使轮廓定位更加精确,有效减少了匹配误差,能够实现图像的高精度快速配准。

     

    Abstract: The fusion analysis of thermal infrared image and visible image is widely used in intelligent security and fault detection. To solve the problem that it is difficult to match two images in the fusion process in the same scene, an image registration method based on featured contour quadrilateral was proposed. Firstly, the thermal infrared image and the visible image were filtered separately by segmentation algorithm. Secondly, the contour points were detected and the contour was redrawn. Then the featured contour was filtered out by the algorithm and the polygon was approximated, and the minimum circumscribed quadrilateral of all contours was generated. The vertexes of this quadrilateral was substituted to calculate the improved homography transformation parameters, and the deviation value of displacement variable was added to neutralize the error of 80%. Finally, the thermal infrared image was registered through the homography transformation model. The experimental results show that this method effectively reduces the matching error, makes the contour positioning more accurate, and can achieve high-precision and rapid image registration.

     

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