Multi-Zone Illumination: Opening New Dimensions for Future Vision Inspection

With the rapid development of machine vision, vision inspection technology is being increasingly widely adopted in manufacturing. Today we share an application case of multi-zone illumination.


Feature：
1. Multi-zone lighting: Traditional light sources often operate with uniform illumination, while multi-zone lighting divides the light source into multiple zones, allowing each zone to be illuminated independently. This provides more precise control for machine vision systems, ensuring optimal visual inspection results.
2. Multi-directional lighting: In many cases, simultaneous illumination from two directions is required to achieve the desired effect. The four-zone lighting solution provides a comprehensive solution, facilitating a more comprehensive analysis and evaluation of the inspection object.

Application：
1. Surface Bump Detection: In the electronics manufacturing, automotive industry, and other fields, multi-zone lighting can help you detect tiny bumps and bumps on product surfaces.
2. Background Defect Detection: When faced with complex backgrounds, multi-zone lighting can highlight the defects of interest, minimize background interference, and improve defect detection accuracy.
3. Character Reading: Whether you need to read characters in the packaging industry, logistics centers, or other fields, the multi-directional lighting of multi-zone lighting can enhance character clarity and provide a higher character reading success rate.
4. Working with Photometric Stereo Algorithms: Our multi-zone lighting works seamlessly with photometric stereo algorithms to provide advanced visual inspection solutions, ensuring more accurate results in complex inspection scenarios.

Imaging instance：
1.Pai Gow point recognition As can be seen from the figure, although traditional ring lighting provides uniform illumination, it lacks contrast. Combining a multi-area light source with a photometric stereo algorithm can achieve clearer image contrast, providing reliable image data for the algorithm's stable recognition.

2.Tire character recognition Imaging the tire from four different directions failed to fully display the characters. By using multi-zone light sources and using the photometric stereo algorithm, we obtained high-contrast images, which provided reliable image data for the algorithm's stable recognition.

3.Metal pit detection The slight bumps on the bearing can be highlighted by single-direction lighting, but the overall effect is almost invisible. However, by imaging the four regions separately and analyzing the 2.5D image processing, the slight bumps can be presented.