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Abstract

A pair of calibration algorithms are provided for calibrating a color camera in a machine vision system. The first and most general form of the calibration algorithm requires that a calibration target be shown to a well adjusted machine vision system. The calibration target contains samples of red, green and blue. A gray level histogram is taken of each of the resulting red, green and blue images and is used to generate corresponding standard cumulative probability functions. The standard cumulative probability functions, together with a copy of the calibration target, is provided to a machine vision system having its own color camera which requires calibration. The same above-noted steps are repeated for this system and the resulting cumulative probability functions are compared to the corresponding standard cumulative probability functions to obtain gains for the red, green and blue channels of the camera to be calibrated . In the second simplified version of the calibration algorithm, a target patch of pure white is provided and camera outputs for red, green and blue are determined while observing the patch. The average gain for each of the output channels of the color camera is determined. This simplifies to taking the average white level measured for each of the channels and dividing the average white value into the full scale value of the machine vision system to be calibrated. Applying the three gain factors determined under either version of the algorithm to a subsequent image allows one to end up with a color-corrected image.

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