CODEWITHSUNDEEP
image-processingcamerapixeldimensionscamera-calibration
Ashwini
Ashwini

Reputation: 31

Is there a way to find mm per pixel value for a camera?

I need to implement dimension inspection of an object with a tolerance of 20 microns using image processing. To measure the dimension in mm, i need the mm per pixel value for pixel to mm conversion.

Camera and lens Specifications: 5 MP Matrix vision camera (2592 x 1944) 25 mm lens

How i tried to do it: I used a 30 cm ruler to get the actual field of view in mm covered by the camera.I got a plot of the image using Matplotlib function in OpenCV as shown in the fig. Image for scaling

From the image i got 31 mm as the actual width covered by the camera and the camera resolution is 2592 x 1944. So i obtained mm/pixel = 31/2952 = 0.011959876. But i want to know if it is the correct way to find the mm/pixel value using a centimeter scale specially when tolerance of 20 micron is needed in dimension inspection. If this is not the correct way, then a solution procedure for finding mm/pixel value would be really helpful.

Upvotes: 3

Views: 4839

Answers (2)

user1196549
user1196549

Reputation:

20 microns over a field of view of 31 mm = 31000 µm corresponds to 1.7 pixel, so your measurement error must be smaller than that. This is a stringent requirement. Your ruler and manual operation are not appropriate.

In the first place, you should check the magnitude of the lens distortion, which could very well exceed these 1.7 pixels. You will need a precise calibration procedure that can fit a deformation model to the image. For this purpose you should use a certified calibration target such as grid of dots or a chessboard pattern.

At the same time as the calibration software measures and compensates the distortion, it will provide the scale factor between physical units (knowing the grid spacing) and pixels. You can measure feature location on the target by blob analysis or gauging techniques, then use least-squares fitting of a model.

Software packages made for machine vision applications do contain such tools.

Also be aware that there can be a bias in the dimensional measurement of the object due to mis-location of the edges. Simply moving the light source can result in variations of the measured size.

If your objects are always the same and at the same place in the field of view, a cheap solution is to establish a repeatable measurement procedure in pixels, and physically measure one of the parts. This will give you a scale factor valid in the same conditions.

But simply moving the object will have a noticeable effect, both by changing the light reflection/shadows on edges and by having a different distortion.

Upvotes: 4

Andrea
Andrea

Reputation: 3077

I believe what you are doing really borderline. First of all, to be as precise as possible I would use the right (or left) edge of the most left and most right ruler ticks like I sketchedenter image description here here:

and then use this value in pixel to calculate the mm/pixel calibration value. Even using this method 20 mu is really tough to achieve. Let's say we can determine the ruler tick edge position with a precision of 2 pixels (very optimistic) then you would have an error of about 31mm/2580 * 2, which is about 25 mu.

If you really need the 20mu calibration precision I would go for a microscope calibration target. I've been always used one of those for this kind of calibration task.

Upvotes: 3

Related Questions