Deep Learning

Choosing Between Machine Vision and Deep Learning

Choosing between Machine Vision and Deep Learning

Application requirements dictate the most appropriate inspection methods

Deep learning-based image analysis and traditional machine vision are complementary technologies, with overlapping abilities as well as distinct areas where each excels. The choice between traditional machine vision and deep learning depends upon:
  • The type of application being solved
  • The amount of data being processed
  • Processing capabilities
Traditional rule-based programming technologies are better at:
  • Gauging and measuring
  • Precision alignment
Deep learning-based image analysis excels at:
  • Complex cosmetic inspection
  • Texture and material classification
  • Assembly verification
  • Deformed and variable feature location
  • Challenging OCR, including distorted print

Some applications may involve both technologies. For example, traditional vision may be the best choice to fixture a region of interest precisely, and deep learning to inspect that region. The result of a deep learning-based inspection may then be passed back to traditional vision to take accurate measurements of the defect size and shape.

When to Deploy Machine Vision vs Deep Learning

Deep learning-based image analysis and traditional machine vision are complementary technologies, with overlapping abilities as well as distinct areas where each excels. Some applications may require or involve both technologies.

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