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A PCB image segmentation model based on rotational X-ray computed laminography imaging.

Liu Shi1,2,3,4, Cunfeng Wei1,2,3,4, Tong Jia1,2,3,4

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This study introduces a novel segmentation model for printed circuit board (PCB) inspection using X-ray computed laminography (CL) imaging. The method effectively suppresses artifacts, enabling accurate extraction of PCB circuit layer information.

Keywords:
CLPCBactive contour modelimage segmentation

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Area of Science:

  • Electronics Manufacturing
  • Non-Destructive Testing
  • Image Processing

Background:

  • Industrialization drives complexity in printed circuit board (PCB) manufacturing, necessitating advanced inspection techniques.
  • X-ray computed laminography (CL) offers high-resolution inspection for large, flat objects, making it suitable for PCB analysis.
  • Exploring CL imaging for PCB inspection is crucial for quality control and integrity.

Purpose of the Study:

  • To develop and validate an effective image segmentation model for extracting PCB circuit layer information from CL images.
  • To address challenges in PCB inspection, specifically aliasing artifacts present in CL data.

Main Methods:

  • A two-component segmentation model was developed for PCB CL images.
  • The first component integrates edge diffusion and l0 smoothing to filter aliasing artifacts.
  • The second component utilizes a fuzzy energy-based active contour model with local pre-fitting energy for segmentation.

Main Results:

  • The proposed model successfully suppresses aliasing artifacts in PCB CL images.
  • Demonstrated good performance across different PCB circuit layers.
  • Simulation experiments confirmed accurate segmentation under ideal conditions.

Conclusions:

  • The developed segmentation model is effective and applicable for PCB inspection using CL imaging.
  • Comparative testing validated the model's superiority over existing methods.
  • This technique enhances the integrity and complexity assessment of PCBs.