畸变图像边缘轮廓的分段拟合

Proceedings of the 2022 5th International Conference on E-Business, Information Management and Computer Science Pub Date : 2022-12-29 DOI:10.1145/3584748.3584756

Lipin Tan, Qiongqiong Wang, Haonan Zheng, Yi Si

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引用次数: 0

摘要

亚像素边缘定位是视觉测量中的一项关键技术，近年来得到了广泛的研究。本文采用高斯拟合算法和基于Zernike正交矩的边缘检测技术提取图像的边缘轮廓，利用BP神经网络确定图像几何畸变的具体形式，通过反向灰度插值法得到积像校正后的目标图像。将微分与拟合相结合，利用matlab计算每个轮廓的长度。通过迭代比较拟合误差和阈值得到轮廓的所有线段点，并将最小二乘拟合到线段区间内的坐标，得到最终曲线方程。

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Piecewise fitting of distorted image edge contour

Subpixel edge localization, a key technique for visual measurement, has been widely studied in recent years. In this paper, gaussian fitting algorithm and Zernike orthogonal moment based edge detection technology are used to extract the edge contour of the image, BP neural network is used to determine the specific form of image geometric distortion, and the target image corrected by product image is obtained by backward gray interpolation method. Differential and fitting are combined, and matlab is used to calculate the length of each contour. The final curve equation is obtained by iteratively comparing the fit error and the threshold value to obtain all the segment points of the profile and fitting the least squares to the coordinates within the segment interval.

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Proceedings of the 2022 5th International Conference on E-Business, Information Management and Computer Science

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