The Research of Knowledge Expression on Image Classification by Using Rough Sets Theory and PCA

• Main Authors: I-Liang Shih, 施奕良
• Other Authors: Tien-yin Chou
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/17678153927752939554

碩士 === 逢甲大學 === 環境資訊科技研究所 === 94 === The ideal of this study is to search a possible solution for the knowledge of rice on image information. This study will use the Rough Sets Theory to build the decision rules of rice displayed in the information system. On the other hand, using the Engine of Knowledge Building with decision rules of Rough Sets Theory can improve the accuracy of classification. There are two point of results for image classification . One will be compared to principle component analysis with statistic normal distribution analysis, the other will improve the Knowledge Base with logical judgment. The contributions to Rough Sets Theory could provide better image classification results than the tradition methods and make it possible to control the knowledge of rice on image information.