Considering the influences of complex indoor environments on the accuracy of visible light positioning, an indoor positioning method based on the visible light fingerprint is proposed. This method uses a positioning terminal to receive the signal strength information generated by different LEDs in a room to construct features, and the physical coordinates are used as labels. Then, a support vector machine regression (SVR) algorithm learning model is adopted to determine the rough position range of a moving target. Simultaneously, to further optimize the positioning performance, a fingerprint positioning algorithm is used to achieve more accurate positioning with the location range as the limiting condition. The proposed positioning method is tested in a spatial region of 4 m×4 m×3 m. The results show that the probability of achieving a positioning error of less than 1 cm is 67.5%. Compared to the SVR positioning algorithm, the proposed method can improve the average positioning error by 93.98%. Compared to the traditional fingerprint-based localization method, the proposed method can achieve more accurate localization with lower complexity. Both the accuracy of the indoor positioning and the utilization rate of the data are effectively improved by the proposed method.