Abstract
There are always some flaws in the industrial alloy due to various factors in the foundry process. Industrial workers still manually classify these flaws. In this paper, we present a method which can do the classification automatically. Images to be classified under any scan voltage are transformed to a standard voltage based on the multiple linear regression algorithm. Then characteristic vectors are extracted automatically. Finally, the image is classified by discrimination function which is computed based on Support Vector Machine (SVM) method. Experiments show that our method produces a good precision.
| Original language | English |
|---|---|
| Pages (from-to) | 451-456 |
| Number of pages | 6 |
| Journal | Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence |
| Volume | 17 |
| Issue number | 4 |
| State | Published - Dec 2004 |
| Externally published | Yes |
Keywords
- Automatic classification
- Industrial CT image
- Multiple linear regression
- Support vector machine
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