摘要： 在传统的几何矩定义的基础上进行扩展，给出了结构矩的定义和计算。其实质是对原有几何矩定义中的密度函数经过变换得到新的密度函数。在此基础上定义的不变矩突出或者扩大了形状之间的差别，因而使形状相似性的比较建立在更为可靠的基础上。基于平方变换的实验表明，与传统的几何矩相比结构矩方法具有更好的效果。

关键词: Hu 矩；结构矩不变量；形状识别

Abstract: Object shape comparability is a challenging problem in the field of pattern recognition and computer vision. The method based on the geometric moment invariants is the typical method in these applications. This paper introduces structure moment invariants based on the geometric moment invariants from transforming the density in geometric moments into a new density. The difference in the shapes is increased by using the structure moment invariants. Therefore, this method can be used in object shape analysis. To support our new theory, an algorithm for object shape analysis is designed and experiments based on square transform are conducted. Experimental results give an encouraging high recognition rate by using the structure moment invariants

Key words: Hu’s moments; Structure moment invariants; Shape recognition