Detection of pinhole defects on chips and wafers using DCT enhancement in computer vision systems |
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Authors: | Hong-Dar Lin Duan-Cheng Ho |
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Affiliation: | (1) Department of Industrial Engineering and Management, Chaoyang University of Technology, 168 Jifong E. Rd., Wufong Township, Taichung County, 41349, Taiwan |
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Abstract: | This paper presents a global approach for the automatic inspection of tiny pinhole defects in randomly textured surfaces of
surface barrier layer (SBL) chips. By means of a discrete cosine transform (DCT)-based image restoration scheme, the proposed
method is independent of textural features and thus not confined by the limitations of feature extraction based methods. Through
properly decomposing the frequency matrix of an image in the DCT domain and selecting the best radius of the sector filter
for the high-pass filtering operation, we effectively attenuate the global random texture pattern and accentuate only tiny
pinhole defects in the restored image. We also develop two accumulative sum detection procedures that automatically determine
the best high-pass filtering parameters based on the abrupt changes of the frequency coefficients in the decomposed matrix.
Experimental results show that the proposed method outperforms the traditional approach in reducing the Type I error by 70–80%
and in decreasing the deviation of the defect areas by 95%. Moreover, the proposed method can be applied to various types
of passive components in large-batch production because no precise positioning of the target chip or template matching is
required. |
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Keywords: | Pinhole defect detection Computer vision system Discrete cosine transform Cumulative sum algorithm Enhancement of frequency domain |
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