基于语义数据模型的木材识别方法

在分析木材识别传统方法的基础上，应用语义学原理对木材识别特征进行聚类分析。利用语义数据模型方法把对象属性进行分解及组合，把属性域分为名称型、程度型、数值型和描述型，对属性域进行系统化、数字化和图形化。采用图形灰度表示取值概率和判断概率，建立并应用木材识别语义数据模型，以提高木材识别智能化程度。经检验，该方法快速、准确，具有较强的模糊识别能力。

A New Wood Identification Method based on Semantic Data Model

By analyzing the traditional wood identification methods,the thesis applies the semantic principle to study the characteristics of the wood identification.With the division and composition of the object's attributes,the attributes domains are divided into four types as noun type,degree type,number type and describing type,and are handled systematically,digitally and pictorially.The method uses the grey to express the probability of getting values and judgement.The thesis sets up the wood identification Semantic Data Model(SDM) to improve the identifying ability.The method based on SDM is rapid and exact,and can identify woods intangibly.The method is innovated in the wood identification applying information management in Chinese.