图像拼接
管道(软件)
人工智能
计算机视觉
失真(音乐)
计算机科学
透视图(图形)
特征(语言学)
透视失真
管道运输
转化(遗传学)
投影(关系代数)
特征提取
点(几何)
图像(数学)
数学
算法
工程类
几何学
基因
哲学
环境工程
生物化学
化学
放大器
程序设计语言
语言学
带宽(计算)
计算机网络
作者
Z. Zhang,Jiazheng Zhou,Xiuhong Li,Chaobin Xu,Xinyu Hu,Linhuang Wang
出处
期刊:Electronics
[MDPI AG]
日期:2024-07-23
卷期号:13 (15): 2898-2898
标识
DOI:10.3390/electronics13152898
摘要
It is common to find severe perspective distortion in a pipeline’s image in medium-diameter pipeline defect detection by the panoramic image unwrapping method, resulting in low-quality image unwrapping and stitching, which is caused by the camera’s optical axis being completely deviated from the pipeline’s center. To solve this problem, a novel correction method for reducing perspective distortion in pipeline images was proposed for pipeline defect detection. Firstly, the method enhances the edges of unevenly illuminated regions within a pipeline to facilitate image segmentation and identify key points necessary for correcting perspective distortion. Then, a six-feature-point extraction method was proposed for a circle target to establish the projection relationship between the extracted feature and mapped points on the reference circle. Finally, a perspective matrix was constructed to complete the perspective transformation correction of the distorted images. The results show that the average correction rate and the average relative error of the proposed correction method can reach 90.85% and 1.31%, respectively. The study innovatively used the enhancement of uneven illumination to find distorted edge information. It proposed an extraction method using a reference circle and six key feature points to build a mapping model. It can provide a novel method which can be used to obtain a superior image for pipeline detection and lay a solid foundation for subsequent high-quality pipeline image stitching.
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