ML Anthology

Automated Inspection of Solder Bumps Using Visual Signatures of Specular Image-Highlights

Rajarshi Ray
CVPR 1989 pp. 588-596
doi:10.1109/CVPR.1989.37906 /cvpr/1989/ray1989cvpr-automated/

Abstract

The author describes a technique for automated inspection of solder bumps by analyzing spatial features and intensity characteristics of image highlights. It is based on high-contrast imaging of specular soldered surfaces against a reflective background using dark-field illumination for selective enhancement of surface topography. Bright-field images of these surfaces are also analyzed to resolve ambiguities in the defect-identification process. The reflectance of solder is studied, for the estimation of corresponding signatures of image specularities, which provide information about surface curvature, metallurgical constituents and topographic discontinuities. During inspection, a specular highlight in the run-time image is mapped into a feature space of reduced dimensionalities for comparison against the features of typical signatures. Based on this principle, visual inspection systems have been designed and implemented for high-speed detection of defective solder bumps and leadless ceramic chip carriers and metallized advanced VLSI wafers.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Ray. "Automated Inspection of Solder Bumps Using Visual Signatures of Specular Image-Highlights." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1989. doi:10.1109/CVPR.1989.37906

Markdown

[Ray. "Automated Inspection of Solder Bumps Using Visual Signatures of Specular Image-Highlights." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1989.](https://mlanthology.org/cvpr/1989/ray1989cvpr-automated/) doi:10.1109/CVPR.1989.37906

BibTeX

@inproceedings{ray1989cvpr-automated,
  title     = {{Automated Inspection of Solder Bumps Using Visual Signatures of Specular Image-Highlights}},
  author    = {Ray, Rajarshi},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1989},
  pages     = {588-596},
  doi       = {10.1109/CVPR.1989.37906},
  url       = {https://mlanthology.org/cvpr/1989/ray1989cvpr-automated/}
}