A complete orthogonal discriminant locality preserving method based on minimal criterion is proposed on the theory of unsupervised discriminant projection. According to the space information among samples belonging to the same class, the proposed method redefines the within-class and between scatter matrix. Then, according to the objective function of unsupervised discriminant projection, the new objective function is derived, which can address the small sample size problem by being projected into total scatter matrix non-null space. The algorithmic procedure of the proposed method based on QR decomposition is given. Finally, experimental results on face database demonstrate the effectiveness of the proposed method.