Fingerprint orientation is the key information in fingerprint enhancement and matching. According to the problem of incomplete fingerprint orientation, a novel algorithm of fingerprint orientation reinstatement is proposed based on Local binary pattern (LBP) and mutual information function. Firstly, mutual information of fingerprint orientation is computed. Secondly, the feature vector is defined for incomplete area classification by Support vector machines (SVM). Then, the fingerprint orientation field of the incomplete area is re-computed and measured by LBP and mutual information function. For orientation reinstatement, LBP is used to measure the similarity of incomplete and complete area, while the mutual information function is used to measure correlation and competition of the neighborhood. Additionally, fuzzy criterion is proposed to assign different weights for neighborhood block and incomplete block for modifying orientation. As a result, the modified fingerprint orientation is used for post-processing. And the performance is shown in the experimental and proves the efficiency and reliability of our algorithm.