Authors:
Yoshiharu Nakamura
1
and
Shuichi Enokida
2
Affiliations:
1
Kyushu Institute of Technology, Mitsui High Tech and Inc., Japan
;
2
Kyushu Institute of Technology, Japan
Keyword(s):
Machine Vision, Defect Detection, Multiple Light Source Imaging, IC Lead Frame.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Image Generation Pipeline: Algorithms and Techniques
Abstract:
It is especially needed for the IC lead frames used in the manufacture of semiconductors, which require both
high quality and miniaturization. To overcome above, automatic defect detection systems based on image
processing methods were proposed. Especially, this paper focuses on methods using the surface normal
direction to detect a deformation in flat parts. Since most of these methods use a fixed parameter, the risk of
missing a defect in industrial parts becomes a problem. In this paper, new defect detection method is
proposed for detecting various defect sizes and defect types. This method determines the appropriate block
size based on the median value of luminance dispersions calculated for several block sizes and learning
from a sample that detects a defect point beforehand. We used 105 samples in our experiments. Our
experimental results show our proposed method selects the superior parameters and identification of the
defect area selected is superior with learning in detectin
g defects of several sizes.
(More)