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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Perner, P. |
| Copyright Year | 1994 |
| Description | Author affiliation: HTWK, Leipzig, Germany (Perner, P.) |
| Abstract | Defect classification by image based techniques is an important issue in quality assurance and nondestructive testing. The solution of the problem is usually complex and context dependent. A domain specific interpretation is required. For this not only knowledge about the appearance of the objects is necessary, but also knowledge about the technological background is required. Thus, the acquisition, representation and use of domain specific knowledge in combination with image processing facilities is a central point. The architecture of a knowledge based defect classification system is described. The architecture is flexible enough to be used for different applications. The performance of the system is described for defect recognition and diagnosis of misprints in offset printing.<> |
| Starting Page | 65 |
| Ending Page | 68 |
| File Size | 285189 |
| Page Count | 4 |
| File Format | |
| ISBN | 078031865X |
| DOI | 10.1109/SIPNN.1994.344964 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1994-04-13 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Printing Image recognition Data acquisition Ink Inspection Signal processing Cameras Control systems Sensor systems Signal detection |
| Content Type | Text |
| Resource Type | Article |
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