摘要
靶标中心定位是红外热成像仪标定过程中的关键技术。针对靶标形貌相对复杂的特点,提出了一种基于自构卷积核改进模板匹配的中心定位算法。首先算法通过构造具有靶标图像特征的归一化模板,在下采样与预处理的目标图像上移动模板进行匹配运算,得到粗定位结果。然后,根据粗定位中心对原图进行兴趣域(Region of Interest,ROI)精细匹配,并通过亚像素细分算法进一步校正。最终,确定准确的靶标中心位置。利用该算法对模拟的劣化环境下靶标图像进行检测,能有效避免模糊、背景复杂、目标不完整或者特征不明显的情况对定位的干扰,具有较好的鲁棒性,能够准确地定位靶标中心,且运算速度快,与互相关(Cross-Correlation,CCORR)、归一化互相关(Normalized Cross-Correlation,NCC)等传统模板匹配和Hough变换相比有较大的提升,可以满足红外热成像仪自动标定过程中的定位需求。
Target center positioning is a critical technology in the calibration process of infrared thermal images.Given the relatively complex morphology of target images,we propose a center positioning algorithm based on improved tem‐plate matching with self-constructed convolution kernels.First,the algorithm constructs a normalized template with tar‐get image features and performs matching operations on subsampled and preprocessed target images to obtain coarse po‐sitioning results.Based on the coarse positioning center,the original image undergoes region of interest(ROI)fine matching,and further correction is achieved through a subpixel subdivision algorithm.Ultimately,the precise target center position is determined.This algorithm effectively detects target images with blurring and indistinct edge features,avoiding interference from blurring,occlusion,complex backgrounds,or indistinct features.It demonstrates good ro‐bustness,accurately positions the target center,and operates at high speed.Compared to traditional template matching methods like cross-correlation(CCORR),normalized cross-correlation(NCC),and Hough transform,it offers signifi‐cant improvements and meets the positioning requirements in the automatic calibration process of infrared thermal imag‐ers.
作者
袁狄剑
许新科
刘通
汪劲雯
杜昱
YUAN Di-Jian;XU Xin-Ke;LIU Tong;WANG Jin-Wen;DU Yu(College of Metrology Measurement and Instrument,China Jiliang University,Hangzhou 310018,China)
出处
《红外与毫米波学报》
北大核心
2025年第3期469-476,共8页
Journal of Infrared and Millimeter Waves
关键词
红外目标检测
中心定位
模板匹配
超分辨率
infrared target detection
center positioning
template matching
super-resolution
作者简介
袁狄剑(1998-),男,浙江诸暨人,硕士研究生,主要研究领域为计算机视觉、图像处理.E-mail:yuandj1998@163.com;通讯作者:许新科,E-mail:xuxinke-123@163.com;通讯作者:刘通,E-mail:18A0202103@cjlu.edu.cn。
