基于Prewitt-Franklin矩的亚像素边缘检测方法
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长春理工大学机电工程学院 长春 130022

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TN29;TP391.4

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军委装备发展部 “慧眼行动”(62502010355)项目资助


Sub-pixel edge detection method based on Prewitt-Franklin moment
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School of Mechanical and Electrical Engineering, Changchun University of Science and Technology,Changchun 130022, China

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    摘要:

    针对传统亚像素边缘检测方法中存在效率低、定位精度不足等问题,提出了一种基于Prewitt算子与Franklin矩融合的亚像素边缘检测算法。所提方法首先通过Prewitt算子实现边缘的像素级初定位,继而构建基于Franklin矩的亚像素边缘分析模型,利用多阶矩卷积提取边缘特征,结合矩函数的正交性与旋转不变性,建立图像旋转前后矩值关联关系,从而精确计算边缘点的亚像素坐标,并通过改进的判别条件完成边缘点的有效筛选。最后,采用最小二乘法对边缘进行拟合。实验结果表明,喷射口检测的平均误差为0.002 6 mm,平均检测时间为0.805 s,并且定位精度更高、抗噪性更强、具有普适性,能够更好地解决图像边缘检测定位精度低及效率慢等问题。

    Abstract:

    Aiming at the problems of low efficiency and insufficient positioning accuracy in traditional sub-pixel edge detection methods, this paper proposes a sub-pixel edge detection algorithm based on Prewitt operator and Franklin moment fusion. Firstly, the Prewitt operator is used to realize the pixel-level initial positioning of the edge, and then the sub-pixel edge analysis model based on Franklin moment is constructed. The multi-order moment convolution is used to extract the edge features. Combined with the orthogonality and rotation invariance of the moment function, the relationship between the moment values before and after the image rotation is established, so as to accurately calculate the sub-pixel coordinates of the edge points, and the effective screening of the edge points is completed by the improved discriminant conditions. Finally, the least square method is used to fit the edge. The experimental results show that the average error of the jet port detection is 0.002 6 mm, the average detection time is 0.805 s, and the positioning accuracy is higher, the noise resistance is stronger, and the universality is better. It can better solve the problems of low positioning accuracy and slow efficiency of image edge detection.

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丁海涛,杨帅,孟凡军.基于Prewitt-Franklin矩的亚像素边缘检测方法[J].电子测量技术,2026,49(9):220-227

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  • 在线发布日期: 2026-06-08
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