Color is used as most an important cue in those studies such as skin detection

face detection and recognition

image and digital video retrieval. But under changing illumination

objects may show different color as the original one it is

especially the lights run out of the range of the camera sensors. In such worse condition

many algorithms become useless. In order to solve this problem

many researchers introduced additional known knowledge about the objects or environment and so have their use limitation. In this paper

an algorithm's architecture is proposed to automatically detect illumination and correct the color of image without use of any additional knowledge and any assumed ideal condition

but the image itself. By analysing the chromatic histogram characters of uncorrected color image in RGB channels

it first detect which channel cause color uncorrected and then use histogram characters above to adjust channel's intension until it reach balance between each channel. A large of different uncorrected color images is used to verify the efficiency of our algorithm

including computer simulating images

face images under different illuminants and images in art and films. The result shows that our algorithm works well in worse condition

and can correct and restore the image to its original color in most circumstance.