Abstract: The problem of pattern recognition based on characteristic vector is often encountered in computer measurement and control system. But the characteristic vectors of existing patterns in database and that of object will be recognized are all to present somewhat uncertainty due to the error from the procedure of extracting them. This research puts fuzzy theory into recognizing procedure with transforming it into a similarity or distance problem of two fuzzy sets. The recognition algorithms based on shortest distance and largest grid similarity degree are provided in this paper, and to be successfully used in personal identification system based on hand shape.

摘要： 在计算机测量与控制系统中经常会遇到基于特征向量的模式识别问题，由于特征向量提取过程所带来的误差，使得数据库中标准模式的特征向量与待识对象的特征向量都具有一定的不确定性。本研究将模糊理论应用于识别过程中，将识别过程转换为两个模糊集的贴近度或距离问题，设计实现了基于格贴近度和距离的识别算法，并成功应用于基于手掌形状的身份识别系统中。