在计算机视觉中，几何形状的识别具有十分重要的意义，而一般几何形状可以分为区域和结构两类。Hu提出的不变矩是用于区域形状识别的几何特征，但对于结构则因不满足缩放不变的条件而不适用。为此对Hu提出的区域不变矩和Chen提出的区域不变矩快速算法进行了扩展，并定义了对于结构和区域均满足平移、缩放、旋转不变的相对矩，从而统一了区域和结构的矩特征计算公式，而且与Hu的不变矩相比，更具有一般性，利用相对矩进行的识别实验表明，相对矩是对区域、封闭和不封闭结构的形状进行识别的有效特征，尤其在识别封闭和不封闭结构时，比傅立叶描述子等传统方法简便。

Shape recognition is a very important problem in computer vision.Geometric shapes can be divided into two classes: regions and single pixel structures.Hu's invariant moments are often used as features for characterizing shapes of regions.However when applied to structures,Hu's moments lose scale invariant.Chen proposed a method based on region boundaries to speed up the calculation of Hu's invariants.In this paper we extend Hu's and Chen's methods to define 10 relative moments,which are independent of position,scale and orientation.The formula of invariant relative moments we proposed can be applied to both regions and structures.Experiments show that the invariant relative moments recognition are effective to shape of regions,closed and unclosed structures.This method is also more convenient than Fourier Descriptors.