Vague集的相似度在智能系统的研究中有着重要的意义,现有的相似度实质上是基于距离来定义的.从蕴涵算子的角度来研究Vague集(值)相似度,给出了一些新的Vague集相似度的计算方法,通过和现有的相似度进行比较分析,证明该方法具有更好的合理性和度量效果,因而有望在模式识别、图象处理等领域中得到广泛的应用. The similarity of Vague sets is of great significance in the research of intelligent systems, and the existing similarities are essentially defined based on distances. The similarity of Vague sets (values) is studied from the point of implication operator, The new method for calculating the similarity of Vague sets is proved to be more reasonable and effective by comparison with the existing similarity, so it is expected to be widely used in the field of pattern recognition and image processing .