视频测量影像序列椭圆形人工目标点快速识别和跟踪方法

A Systemic Algorithm of Elliptical Artificial Targets Identification and Tracking for Image Sequences from Videogrammetry

针对视频测量建筑物健康监测获取海量影像序列数据快速、准确识别和跟踪目标点的需求,提出基于影像块技术的椭圆形目标点识别和跟踪完整算法。该算法采用影像分块技术降低数据处理量,实现椭圆形目标点跟踪,集成数学形态学和椭圆几何属性特征,消除图像块边缘检测的非椭圆边缘信息,实现椭圆轮廓的提取,并采用最小二乘法拟合椭圆中心实现亚像素定位,快速、准确地实现视频测量建筑物健康监测椭圆形目标点的识别与跟踪。试验结果表明该方法获取的椭圆中心点像素坐标的RMS残差优于0.025个像素,且相对于随机Hough变换和模板识别算法,跟踪效率提高5倍以上。

In order to satisfy the requirement of identification and tracking the elliptical artificial targets fast and accurately for the image sequences from videogrammetric measurement for structural health monitoring,this paper proposes a systemic algorithm to identify and track the elliptical targets using the image block technique.The proposed method extracts the image block from original images to reduce the amount of data processing for the oval targets tracking.The mathematical morphology and elliptical geometric characteristics are integrated to eliminate the non-elliptical edge information to extract the elliptical contour in the range of image block.At last,the sub-pixel center location for elliptical artificial targets is acquired by the least square algorithm.The experimental results show that RMS error of 0.025 pixel can be achieved by the proposed method,furthermore,compared with the random Hough transform and template recognition algorithm,the tracking efficiency is improved over 5times.