| Project/Area Number |
08660065
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
蚕糸・昆虫利用学
|
|---|
| Research Institution | YOKOHAMA NATIONAL UNIVERSITY |
|---|
Principal Investigator |
TAJIMA Fumiaki Yokohama National Univ., Faculty of Education and Human Sciences, Associate Professor, 教育人間科学部, 助教授 (10236523)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
ISHIGURO Yoshio Yokohama Center for Quality Control and Consumer Service, Dept.of Measurement an, 研究部, 検査計測研究室長
|
|---|
| Project Period (FY) |
1996 – 1998
|
| Project Status |
Completed (Fiscal Year 1998)
|
| Budget Amount *help |
¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 1998: ¥400,000 (Direct Cost: ¥400,000)
Fiscal Year 1997: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1996: ¥1,300,000 (Direct Cost: ¥1,300,000)
|
|---|
| Keywords | Raw Silk Testing / Cleanness and Neatness Defects / Classification of Defects / Analysis of Visual Processing / Automatic Testing System / Fuzzy System / 視覚情報処理 / エッジ / ファジィルール / パターン認識 / 節検査 / エッジ検出 |
|---|
| Research Abstract |
To automate the raw silk test, this study was done. The defects test system which is able to classify all the defects as isolated ones has been developed in the previous year. However, two minor defects or more are for instance adjacent, the appearing defects is grouped, and they are judged one major defect in an actual test occasionally. To solve such edge extraction problem, 1998 fiscal year, we examined the classification of two or more adjacently appearing defects. As a result, the computer model of the edge extraction process of the defects by which the fuzzy theory was applied was constructed based on the results of the visual information process when the inspection personnel tested the defects by the previous year. The constructed model uses fuzzy rule sets, and has the edge extraction rule part and the flat part extraction rule part. The process of the system was explained as follows : first, the edges of all the appearing defects were extracted as isolated defects based on the edge extraction rules using fuzzy inference. Second, some of the extracted defects were classified as adjacent defects based on the flat part extraction rules using the same inference. The classification rate of the defects of the new system was able to be improved by this method by about 5%, compared with the old one.
|
