Illumination compensation methods for automatic fiber connector inspection.

Area of Science:

• Computer Vision
• Optical Engineering
• Materials Science

Background:

• Automatic machine visual inspection systems for fiber connectors face challenges with uneven image illumination.
• This uneven lighting complicates the process of converting grayscale images to binary images for defect identification.

Purpose of the Study:

• To propose effective methods for compensating unevenly distributed image illumination.
• To enable the use of standard image processing techniques for fiber connector defect detection.

Main Methods:

• Developing and implementing image processing algorithms to correct for non-uniform lighting.
• Applying these compensation methods to grayscale images of fiber connectors.

Main Results:

• Successful compensation of uneven illumination in images.
• Improved ability to apply standard image processing for defect detection.
• Accurate separation of surface defects like blobs and scratches from the connector background.

Conclusions:

• The proposed methods effectively address the problem of uneven illumination in fiber connector inspection.
• Standard image processing techniques can be reliably used for defect detection after illumination compensation.
• Enhanced accuracy in identifying surface defects such as blobs and scratches is achieved.