说明：  对灰度差绝对平均值算法匹配次数多，不具有旋转不变性等缺点，提出一种新的目标识别方法。匹配准则采用具 有环形结构的子窗口内的像素差加毂和的形式表示，保证了算法具有旋转不变性。对模板图像中的特征点按照匹配准则分 别在目标图像中找到相应的匹配点，从而完成匹配操作，与传统的相关匹配算法相比，大大减少了匹配次数。对于因遮挡而 丢失的特征点，可根据已匹配特征点之问的相对距离来重新确定，从而实现目标识别的功能。仿真实验验证了该算法的有 效性。
(A new target recognition method was proposed to improve the rotation invariancc and reduce the matching frequency for nu“mum absolute difference．The rrIatching furlction was the weighted sumof pIx— els difference in sub—windows． The subwindaws were ring-shaped，which made the algorithm have the property of rotation invariance． Feature points matching between trac ki“g window and template could be completed according to the matching functiom(bmpare to conventional algorithm，the matching frequency is reduced The Iost feature points in tracking window could be determined according to the positions of the feature points nlatched．Simulation results prove the validity of the method．)