Optimization of Harris corner detection algorithm for line array infrared image of terminal sensitive projectile
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摘要: 针对Harris角点检测算法对于弹载线阵列红外图像检测角点数量过少及精度较低等问题，提出一种改进算法。首先利用Canny算子检测目标边缘以确定目标区域，再采用三阶B样条梯度算子对目标区域滤波获得M矩阵，然后使用三阶B样条函数与高斯窗口函数的卷积代替原高斯窗口函数对M矩阵进行平滑滤波，进行角点提取，最后在非极大值抑制时采用自适应阈值，以去除伪角点。实验结果表明，文中算法与Harris算法相比，不仅增加了角点的提取数量，在算法的总运行时间上缩减了3/4。
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关键词:
- Harris角点检测 /
- B样条函数 /
- 弹载 /
- 红外图像
Abstract: An improved Harris corner detection algorithm was proposed to solve the problem that the number of detection corners was too few and the accuracy was low when detecting infrared images. Firstly, the Canny operator was used to detect the target edge to determine the target region, and then the cubic B-spline gradient operator was used to filter the target area to obtain the M matrix. Then the convolution of the cubic B-spline function and the Gaussian window function was used to replace the original Gaussian window function for data filtering, and extract the corner points of the target area. Finally, the adaptive threshold was used for non-maximum suppression to remove false corners. The experimental results show that compared with the Harris algorithm, the proposed algorithm not only increases the number of corners points extracted, but also reduces the running time of the algorithm by 3/4.-
Key words:
- Harris corner detection /
- B-spline function /
- missile-borne /
- infrared image
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