We developed a model that can operate similarly to human categorical color perception. The color of an object is not exclusively determined by the reflection spectrum from the surface of the object but is greatly affected by the ambient environmental conditions and depends upon color constancy, The mechanism of color constancy, however, is not explained in detail so acquiring the cognition of the categorical color name of objects under different illuminations is difficult. To that end, the relationship between the chromaticity and the categorical color perception of colored chips under different illuminations is the product of a categorical color-naming experiment was learned by using a neural network. The results showed that the obtained neural network has similar characteristics to those of human vision system.