In the field of machine vision, color constancy is an important factor in achieving computer vision color correction and maintaining the machine stability to color recognition. By means of the psychophysics, the model gains the color perception data obtained by the human eyes perception, and puts it into the neural network for sample training, then optimizes the connection weights and thresholds of the BP neural network using the genetic algorithm. The color constant perception model is applied to the image color correction, and the correction results are evaluated in terms of the subjective and objective measures, the results show that the established algorithm has high precision and better efficiency, low complexity and less error than the classical algorithm, the color representation of images is more consistent with human perception.