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A PCB Alignment System Using RST Template Matching with CUDA on Embedded GPU Board.

Minh-Tri Le1, Ching-Ting Tu2, Shu-Mei Guo1

  • 1Department of Computer Science and Information Engineering, National Cheng Kung University; No.1 University Road, Tainan City 701, Taiwan.

Sensors (Basel, Switzerland)
|May 15, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces an accelerated embedded system for printed circuit board (PCB) alignment using a rotation, scale, and translation (RST) algorithm. The system significantly reduces matching time and enhances precision for critical PCB manufacturing steps.

Keywords:
GPUPCB manufacturingalignment systemembedded systemparallel programmingtemplate matching

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Area of Science:

  • Manufacturing Engineering
  • Computer Vision
  • Embedded Systems

Background:

  • Fiducial mark-based alignment is crucial for printed circuit board (PCB) manufacturing.
  • Machine vision techniques are essential for detecting fiducial marks and aligning PCBs.

Purpose of the Study:

  • To develop an efficient embedded PCB alignment system.
  • To improve the speed and accuracy of fiducial mark detection and alignment.

Main Methods:

  • Employed a rotation, scale, and translation (RST) template-matching algorithm for fiducial mark localization.
  • Implemented parallel processing on a graphics processing unit (GPU) to accelerate the RST algorithm.
  • Optimized the normalized cross-correlation (NCC) formula and feature selection to reduce matching time.

Main Results:

  • Achieved a 32x speed improvement compared to conventional central processing unit (CPU) implementations for a 1280x960 pixel image.
  • Attained a high alignment precision with a tolerance of 36.4μm.
  • Successfully reduced scanning and matching times through parallel GPU processing and algorithmic optimizations.

Conclusions:

  • The proposed embedded system offers a significant advancement in PCB alignment speed and accuracy.
  • GPU acceleration and optimized algorithms are effective in overcoming computational challenges in machine vision alignment.
  • The system provides a robust solution for critical steps in modern PCB manufacturing.