With the rapid development of technology, verification code technology in the network protection and information security has a wide range of applications. Since the means of network attacks are upgraded, verification code technology is also continuously improved. The campus network verification code used in this paper is the most common type of character verification codes of the current network. It is of the characteristics of diversified background noise and character distortion adhesion, so the code is difficult to achieve automatic recognition program. For these characteristics, this paper proposes a RGB de-noising method in the background de-noising stage, and adopts a segmentation method which combines contour difference projection method with the water droplets algorithm in the single character cutting stage. Finally, all the character models are get, KNN algorithm is used for character recognition so as to receive recognition results. Experiments show that the method is of good recognition effects for the verification code with background noise and distortion adhesion character.