How photo quality affects the printed card
Honestly this is probably the biggest noob question everyone has, and yeah photo quality matters more than people think. Blurry or uneven lighting shows right up in print, especially around the signature background area. If you're taking ID photo at home, just grab some soft even light with no harsh shadows and shoot against a plain wall.
Also, read the sticky before posting more, it covers most of this already. Saves everyone time.
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The relationship between the photo you submit and what appears on the finished card is not as direct as it might seem. The vendor's production process transforms the photo through several steps, and what goes wrong in those steps is largely determined by what quality went in.
Resolution and printing
ID card photo zones are small — typically around 22mm by 28mm on a standard license. At 300 DPI (standard for quality printing), that zone requires about 260 by 330 pixels. Your submitted photo gets scaled down to fit this zone. A 2 megapixel photo provides more than enough resolution for this final output size.
Where resolution problems arise is in the scaling algorithm — downscaling a low-quality photo to ID size can amplify artifacts that were barely visible at full size. Compression artifacts, noise, and soft focus that seem minor in a full-size phone photo become more visible when the image is rendered at ID scale. Starting with a sharp, clean source image gives the vendor's system less to work with that could produce visible artifacts.
Lighting and color
The vendor's production process color-corrects the photo for printing. This correction is calibrated for photos taken in standard natural or studio lighting. Photos taken under unusual lighting — warm tungsten, mixed color temperature, strong overhead shadows — may be corrected in ways that shift skin tones unexpectedly. If your photo looks fine on screen but the card face looks off-color, the lighting conditions of the original photo are usually the cause.
Background and edge detection
Vendors often separate the subject from the background using automated edge detection. A clean, high-contrast separation between the subject's face and a uniform background makes this detection accurate. A background that is close in tone to skin, or a subject with flyaway hair creating irregular edges, can cause the detection to cut into or around the face incorrectly.
Taking the photo against a clean, solid-color background with clear separation gives the vendor's system the cleanest input to work with at every processing step.