A new algorithm is proposed to segment color image automatically using the intersecting cortical model with the reference of traditional color image segmentation method. The algorithm converts images into HSV color space and selects one of the H

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and V components with the decision rule of maximum entropy. And it has increased the processing speed greatly compared with traditional color image segmentation method which deals with the three components individually and then merges the results. Our new algorithm costs 257 s

while about one-third of that of the traditional color image segmentation method uses 7533 s. The automatic segmentation with less artificial sets and high accuracy is realized by introducing the maximum cross entropy decision rule into the intersecting cortical model. The new algorithm was compared to the image segmentation method based on max entropy. And the simulation results show that the new algorithm has good performance in color image automatic segmentation.