一种基于紫外成像特性的目标质心提取算法

A Target Centroid Extraction Algorithm Based on UV Imaging Characteristics

为解决传统目标质心提取算法对紫外目标质心提取精度低、影响目标定位精度等问题,本文提出了一种基于紫外成像特性的目标质心提取算法。首先,根据紫外器件成像特性,确定目标区域灰度分割阈值,对紫外图像逐像素进行灰度概率累计分布统计,剔除背景杂散波干扰影响,得到经过时域滤波图像;其次,应用连通域提取方法对滤波后图像中目标进行提取;最后,应用一阶矩质心提取算法获取紫外目标质心。试验结果表明,与传统目标质心提取算法相比,本文所提算法受背景噪声影响较小,质心提取精度高,对紫外图像中各类目标质心提取具有普适性。

Traditional target centroid extraction algorithms have low accuracy for UV target object which affects the target positioning accuracy.In order to solve the problem,a target centroid extraction algorithm based on UV imaging characteristics is proposed.Firstly,according to the imaging characteristics of the UV device,the gray segmentation threshold of the target area is determined,the gray probability cumulative distribution statistics of the UV image is carried out pixel by pixel,and the influence of background stray wave interference is eliminated to obtain the time-domain filtered image.Secondly,the connected domain extraction method is used to extract the target in the filtered image.And finally,the centroid of UV target is obtained by using the first-order moment centroid extraction algorithm.The experimental results show that the proposed algorithm is less affected by background noise and has higher centroid extraction accuracy when compared with traditional algorithms,and it is universal for all kinds of target centroid extraction in UV targets.