The work aims to propose a technology to enlarged storage capacity of QR code, with respect to the deficient information embedding ability of black and white QR code and the demand of large-capacity information storage. Black and white QR code only had two encoded modules which were black and white, and each module stored 1 bit of data. While color QR code had 2n color encoded modules, and each encoded module could store N bits of data. In such case, the storage capacity of color QR code was directly expended by n times. Based on HSV color space model, three-tuple color matching model was applied in color matching of encoded modules to reduce the aliasing effect between color encoded modules. Image contrast enhancement algorithm and K-Means clustering algorithm were used to deal with color deviation of color encoded modules. The data storage performance of color QR code with 16 colors of encoded modules was analyzed. Based on the analysis, when a certain amount of data was stored, the version of color QR code was lower than that of the black and white QR code, and its symbol was smaller. By doing so, the storage capacity of QR code was directly expanded. With QR code direct expansion technology, the storage capacity multiplier can be achieved; with K-Means clustering algorithm, the aliasing effect between the encoded modules of QR code can be greatly reduced, and the decoding accuracy of color QR codes is significantly improved.