Studies on expert system of tree distingushed for education using photo-database

近两年来，我们对树木识别专家系统进行了研究。本研究的目的是提出一种树木辨识的知识，并建构一个原型专家系统。针对如何利用照相机、摄像机、数码相机采集树木照片数据，并进行整理和照片数据库的维护，提出了一些方法。利用PC机编制了照片数据库的维护和反求程序。其次，我们建立了两个专家系统的树木区分对64种京都大学森林在北海道使用专家壳。推导的方法是目前比较流行的IF-THEN方法。根据每棵树的具体特征（叶片形状、叶脉形状等）排列分类索引，构建知识库。从演绎路径分析，似乎所有的分类指标都没有必要区分。第一个专家系统类似于植物书的参考。该方法是一种利用分类指标进行分支演绎的方法。叶长、叶宽采用富士推估法。第二个专家系统与第一个专家系统相同，直到中间分类。经过中间分类后，所有推荐的树都显示在显示器上，并附有照片和分类指标。如果用户选择其中一个与对象树的分类索引相对应，则显示树的特征。对于不了解分类索引术语含义的初学者来说，这种方法对学习如何区分树名很有用。

We studied on expert system of tree distinguished during past two years. The objects of this studies are to appear a knowledge for tree distinguished and to construct of prototype expert system. We get some methods according to how to gather photo-data of tree using camera, video and digital camera, to arrange them and to maintain photo-database. We make some programs of photo-database for maintenance and reverse using P.C..Next, we construct two expert systems of tree distinguished against 64 species on a Kyoto University forest in Hokkaido using expert shell. The method of deduction is IF-THEN method that is popular. We arranged classify indexes according to specifics of each tree which are a shape of leaf, a form of leaf vein and etc.and constructed knowledge database. Analyzing for path of deduction, it was appear that all classify indexes are not necessary to distinguish. The first expert system is similar to reference of a plant book. That is a spreading into branch deduction method using some classify indexes. The technic of Fuji deduction is used for length and width of leaf. The second expert system is same to the first until middle classify. After middle classify, all proposed trees are shown at display with their photograph and classify indexes. If user selects one of them that is corresponding to classify indexes of object tree, the tree characteristic is shown. For a beginner who doesn't understand a mean of classify index's term, this method is useful to learn how to distinguish tree names.