Camera image resolution is defined by the number of pixels in a given CCD or CMOS sensor array. This will be identified in a camera data sheet and shown as the number of pixels in the X and Y axis (i.e 1600 x 1200 pixels).
The application will determine how many pixels are required in order to identify a desired feature accurately. This also assumes you have a perfect lens that is not limiting resolving the pixel (see Demystifying lens specifications). In general more pixels is better and will provide better accuracy and repeatability.
If for example you have a dark hole on a white background filling your field of view (FOV) by 90%, you will have many pixels across the feature. On the contrary, if we have a small pin hole that is within the same field of view, we may not have enough pixels across the hole to identify the feature. In order to find an edge you need at a minimum of 2 pixels given excellent contrast. In order to be robust you ideally will want 3-4 pixels across a edge or feature.
This leads us to identifying the resolution required given the size of a feature. We will do this with an example and provide the needed formulas on how to calculate the resolution.
Example: The vision inspection is to locate a pin hole which is 0.25mm in diameter on a part which is 20mm square. In order to compensate for any misplacement of the part, we will set our FOV to 40mm x 30mm. We would also like to have a minimum of 4 pixels across the 0.25mm feature.
We can calculate the resolution required as follows:
Where:
Rs is the spatial resolution (maybe either X or Y)
FOV is the field of view dimensions (mm) in either X or Y
Ri is the image sensor resolution; number of pixels in a row (X dimension) or column (Y dimension)
Rf is the feature resolution (smallest feature that must be reliably resolved) in physical units (mm)
Fp is the number of desired pixels that will span a feature of minimum size.
For this case we know:
FOV(x) = 40mm
Rf = 0.25mm
Fp = 4 pixels
Calculating the spatial resolution (Rs) needed:
Rs = Rf / Fp = 0.25mm / 4 pixels = 0.0625mm pixel
From the spatial resolution (Rs) and the field of view (FOV), we can determine the image resolution (Ri) required (we have only calculated for the x-axis) using this calculation:
Ri = FOV / Rs = 40mm / 0.0625 mm/pixel = 640 pixels
We have now determined that we need a minimum resolution of 640 pixels in the x-axis to provide 4 pixels across our feature that is 0.25mm in diameter. The camera resolution can now be selected! In today’s world, we could select a VGA (640 x 480) camera for the application. As a note, the number of pixels required depends on many aspects of lighting, optics and algorithms used for processing. This calculation method assumes optimum conditions.
If you do not like math, you can download our resolution calculator here and just enter the data. This makes it easy to test various iterations. Download the calculator HERE.
If you visit our camera page, you can sort by resolution in X and Y resolutions to quickly ID cameras that meet your resolution needs.
For all your imaging needs, you can visit www.1stvision or contact us! to discuss your application in further detail or receive a quote on a desired camera. We can also help identify which sensor is best based on the imaging conditions.
