亚像素直线检测测量通过机器视觉

A. G. Flesia, G. Ames, G. Bergues, L. Canali, C. Schurrer
{"title":"亚像素直线检测测量通过机器视觉","authors":"A. G. Flesia, G. Ames, G. Bergues, L. Canali, C. Schurrer","doi":"10.1109/I2MTC.2014.6860776","DOIUrl":null,"url":null,"abstract":"External visual interfaces for high precision measuring devices are based on the segmentation of images of their measuring reticle. In this paper, a method for subpixel straight lines detection is presented and tested on images taken from the reticle of a dark field autocollimator. The method has three steps, the sharpening of the image using a version of the Savitzky-Golay filter for smoothing and differentiation, the construction of a coarse edge image using Sobel filters, and finally, the subpixel edge location determination, by fitting a Gaussian function to orthogonal sections of the coarse edge image.We discuss results of applying the proposed method to images of the reticle of a Nikon 6D autocollimator, using the scale of the device as a benchmark for testing the error in the location of the lines and compare them with Sobel/Hough and Sobel/polynomial fitting. We report that for this type of image-content, Gaussian fitting has smaller uncertainty, when cameras with two different sensors are used.","PeriodicalId":331484,"journal":{"name":"2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"Sub-pixel straight lines detection for measuring through machine vision\",\"authors\":\"A. G. Flesia, G. Ames, G. Bergues, L. Canali, C. Schurrer\",\"doi\":\"10.1109/I2MTC.2014.6860776\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"External visual interfaces for high precision measuring devices are based on the segmentation of images of their measuring reticle. In this paper, a method for subpixel straight lines detection is presented and tested on images taken from the reticle of a dark field autocollimator. The method has three steps, the sharpening of the image using a version of the Savitzky-Golay filter for smoothing and differentiation, the construction of a coarse edge image using Sobel filters, and finally, the subpixel edge location determination, by fitting a Gaussian function to orthogonal sections of the coarse edge image.We discuss results of applying the proposed method to images of the reticle of a Nikon 6D autocollimator, using the scale of the device as a benchmark for testing the error in the location of the lines and compare them with Sobel/Hough and Sobel/polynomial fitting. We report that for this type of image-content, Gaussian fitting has smaller uncertainty, when cameras with two different sensors are used.\",\"PeriodicalId\":331484,\"journal\":{\"name\":\"2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I2MTC.2014.6860776\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2MTC.2014.6860776","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25

摘要

高精度测量设备的外部视觉界面是基于其测量线的图像分割。本文提出了一种亚像素直线检测方法,并对暗视场自准直仪的十字线图像进行了测试。该方法有三个步骤,使用Savitzky-Golay滤波器对图像进行平滑和微分,使用Sobel滤波器构建粗边缘图像,最后通过对粗边缘图像的正交截面拟合高斯函数来确定亚像素边缘位置。我们讨论了将所提出的方法应用于尼康6D自准直仪的十字线图像的结果,使用设备的比例作为测试线位置误差的基准,并将其与索贝尔/霍夫和索贝尔/多项式拟合进行比较。我们报告说,对于这种类型的图像内容,高斯拟合具有较小的不确定性,当相机与两个不同的传感器使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sub-pixel straight lines detection for measuring through machine vision
External visual interfaces for high precision measuring devices are based on the segmentation of images of their measuring reticle. In this paper, a method for subpixel straight lines detection is presented and tested on images taken from the reticle of a dark field autocollimator. The method has three steps, the sharpening of the image using a version of the Savitzky-Golay filter for smoothing and differentiation, the construction of a coarse edge image using Sobel filters, and finally, the subpixel edge location determination, by fitting a Gaussian function to orthogonal sections of the coarse edge image.We discuss results of applying the proposed method to images of the reticle of a Nikon 6D autocollimator, using the scale of the device as a benchmark for testing the error in the location of the lines and compare them with Sobel/Hough and Sobel/polynomial fitting. We report that for this type of image-content, Gaussian fitting has smaller uncertainty, when cameras with two different sensors are used.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信