图像序列的运动目标选择技术  

The Selection Techniques of Motion Target in an Image Sequence

作　　者：李金宗[1] 韩忠芳[1] 马子墨 

机构地区：[1]哈尔滨工业大学,340信箱哈尔滨150001

出　　处：《电子学报》1998年第9期34-39,共6页Acta Electronica Sinica

摘　　要：本文利用最小二乘法导出了图像局部灰值分布的二元二次多项式系数的最佳估计量，并且把剩余成份看成零均值白噪声，由此建立了二次型模型，它是对局部灰值分布的最好逼近．为了从图像序列中检测帧间变化，基于二次型模型导出了服从F（n＋3，2n－12）分布的统计假设检验模型，其中n为检测窗内的象素数目．因为只有F检验一般还不能够从变化检测中选择出运动目标，本文利用专门设计的聚类分析和补空洞技术，能使目标损失和虚警趋近于零．对于可见光和红外图像序列的实验结果充分说明了所建立的技术路线及其关键技术的有效性和兼容性.In this paper, the optimal estimators of the coefficients of a second-order bivariate polynomial for piecewise grayvalue distributions of image are derived by using the least quadrate multiplication,and the remaning components within eath patch can be attributed to white noise with zero meanvalue.Therefore, the quadratic model is set up, which is the best approacl to piecewise grayvauc distributions.In order to detect changes between consecutive frames, the statistical assumption test model which follows F-distribution with degrees of freedon(n+ 3, 2n-12) is detived based on the quadratic model,where n is the number of pixels in detection window. Because singe motion target can not be generally selected from the detected changes if there is noly F-test, the techniques of clustering analysis and filling holes are also designed, which can make the target loss and false alarm appronch to zerr. The experimental results made with the television-and infrared image sequences fully show the validity and compatibility of the technique route and key techniques proposed.

关 键 词：图像序列 二次型模型 统计假设检验 聚类分析 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]