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基于亚像素定位的图像边缘检测策略研究

刘浩 任宏 赵丁选 孙海超 姜金辰 姜瑞凯

农业机械学报2024,Vol.55Issue(2):242-248,294,8.
农业机械学报2024,Vol.55Issue(2):242-248,294,8.DOI:10.6041/j.issn.1000-1298.2024.02.023

基于亚像素定位的图像边缘检测策略研究

Image Edge Detection Strategy Based on Sub-pixel Location

刘浩 1任宏 1赵丁选 2孙海超 1姜金辰 1姜瑞凯1

作者信息

  • 1. 中国科学院长春光学精密机械与物理研究所,长春 130033
  • 2. 燕山大学机械工程学院,秦皇岛 066004
  • 折叠

摘要

Abstract

Image edge detection is a technique that extracts mutation information from images and is widely used in the fields of image processing and computer vision.The effectiveness of image edge detection directly affects the accuracy of subsequent region information extraction,target recognition,and pose measurement.Taking into account two factors:local extremum and gradient direction,and combining with the trend of image edge direction,a single-pixel edge tracking strategy was proposed for the edge detection problem of low contrast and edge blurred images.Compared with the widely used Canny algorithm,this tracking strategy did not require setting a global threshold,and its implementation was more concise and efficient.The extracted image edges were continuous,smooth,and complete,effectively reducing redundant pixels at the image edges,thereby improving the efficiency of subsequent image processing.Edge tracking direction had strong anti-interference ability and robustness.In order to reduce the deviation between the detected image edge and the real image edge,and improve the accuracy of image edge detection,the adjacent gray values of edge pixels were referred to,and the gradient distribution of edge pixels was used as the basis for sub-pixel localization of that pixel.Through experimental verification,the sub-pixel optimized image edge detection strategy can be used to detect images with blurred edges and low contrast.The detected image edges were complete,continuous,and smooth.This strategy effectively eliminated truncation errors introduced in program operations,improved the accuracy of image edge detection,which was suitable for high dynamic imaging scenes with a brightness range of 5~100 000 lx.

关键词

图像处理/边缘检测/亚像素定位/单像素跟踪/鲁棒性/高动态

Key words

image processing/edge tracking/sub-pixel location/single-pixel edge tracking/robustness/high dynamic

分类

信息技术与安全科学

引用本文复制引用

刘浩,任宏,赵丁选,孙海超,姜金辰,姜瑞凯..基于亚像素定位的图像边缘检测策略研究[J].农业机械学报,2024,55(2):242-248,294,8.

基金项目

国家自然科学基金项目(U20A20332) (U20A20332)

农业机械学报

OA北大核心CSTPCD

1000-1298

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