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A rotation-invariant and nonreferential approach for Ball Grid Array ( BGA ) substrate conduct paths inspection
| Content Provider | Semantic Scholar |
|---|---|
| Author | Yeh, Chia Hua |
| Copyright Year | 2003 |
| Abstract | The aim of this paper is to locate and classify boundary defects such as open, short, mousebite, and spur on Ball Grid Array (BGA) substrate conduct paths using machine vision. Boundary defects are detected by a boundary-based corner detection method using covariance matrix eigenvalues. Detected defects are then classified by discrimination rules derived from variation patterns of eigenvalues and the geometrical shape of each defect type. Real BGA substrates with both synthetic and real boundary defects are used as test samples to evaluate the performance of the proposed method. Experimental results show that the proposed method achieves 100% correct identification for BGA substrate boundary defects under a sufficient image resolution. The proposed method is invariant with respect to the orientation of the BGA substrates, and it does not require pre-stored templates for matching. This method is suitable for various types of BGA substrates in small batch production because precise positioning of BGA substrates and the prestored templates are not necessary. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://machinevision.iem.yzu.edu.tw/english_version/tech/PCB2-ARotationInvariant.PDF |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
