基于OpenCV与Python的高精度零件尺寸测量技术问询

Hey everyone, let me share the precision-focused work I'm doing for my machine vision project right now:

I'm building a high-precision part dimension measurement system using OpenCV and Python. Since the tolerance requirements for the parts are extremely strict, I'm starting with a dedicated precision study to validate the system's repeatability before full deployment.

Here's the core hardware I'm using:

• Basler 5MP industrial camera (model: aca-2500-14gm)
• 100mm×100mm red backlight (the target part is roughly 60mm in size, so the backlight provides full, uniform coverage)

To isolate and measure the system's inherent repeatability, I've designed this test:

The goal is to quantify how consistent the edge detection/measurement results are when the physical setup is completely unchanged.

• Securely place the target part on the red backlight, ensuring it's fully seated and not shifted
• Lock the positions of the camera, backlight, and part—no movement whatsoever during testing
• Capture 100 consecutive images of the stationary part

Next steps will involve using OpenCV for preprocessing (thresholding, edge detection) to extract the part's edge pixel coordinates, then analyzing the 100 sets of measurements to calculate metrics like standard deviation and maximum error range. This will tell me if the system meets the tight tolerance requirements.

内容的提问来源于stack exchange，提问作者Abhijit Balaji