CAJ | 학술논문

利用编码元和非编码元,根据标记点的尺寸、形状及灰度变化等特征提取目标,然后利用非编码元与编码元的不同形状与灰度特征,提出一种改进的编码元自动身份识别方法,同时实现非编码元与编码元的分类;并利用质心定位方法抽取标记点中心位置,抽取的中心具有亚像素级.在利用编码元的身份信息实现同名编码元匹配的基础上,由相似性和相容性确定非编码元的初始匹配,通过3个准则从非编码元的初始匹配中剔除误匹配,最终得到同名非编码元的匹配结果.经实验验证,该算法速度快、匹配率高、鲁棒性好.
이용편마원화비편마원,근거표기점적척촌、형상급회도변화등특정제취목표,연후이용비편마원여편마원적불동형상여회도특정,제출일충개진적편마원자동신빈식별방법,동시실현비편마원여편마원적분류;병이용질심정위방법추취표기점중심위치,추취적중심구유아상소급.재이용편마원적신빈신식실현동명편마원필배적기출상,유상사성화상용성학정비편마원적초시필배,통과3개준칙종비편마원적초시필배중척제오필배,최종득도동명비편마원적필배결과.경실험험증,해산법속도쾌、필배솔고、로봉성호.
Based on the coded and non-coded targets, the targets are extracted from the images according to their size, shape and intensity etc., and thus an improved method to identify the unique identity(ID) of every coded target is put forward and the non-coded and coded targets are classified. Moreover, the gray scale centroid algorithm is applied to obtain the subpixel location of both uncoded and coded targets. The initial matching of the uncoded target correspondences between an image pair is established according to similarity and compatibility, which are based on the ID correspondences of the coded targets. The outliers in the initial matching of the uncoded target are eliminated according to three roles to finally obtain the uncoded target correspondences. Practical examples show that the algorithm is rapid, robust and is of high precision and matching ratio.