A method combined the modified Lucas-Kanade Gait Flow Image (LK-GFI) with the view was proposed to solve the problem that personal identification based on a gait is sensitive to view change. The Lacus-Kanade optical method was used to compute the optical flow between two silhouettes to construct LK-GFI, and the view was obtained according to the walking direction of the person. The LK-GFI database for the target at different views was established, then the new person's view and LK-GFI were extracted. At last, the similarity between the new persons LK-GFI and the targets LK-GFI at the same view was computed by the Euclidian distance method. The performance of this method was evaluated on the data in the CASIA database and the data obtained in indoor lab environment, and the False Rejection Rate (FRR) is 7.95% and 9.12% respectively. It is reduced by 12.5% and 14.45% respectively compared with that of the Gait Energy Image (GEI), and by 7.77% and 6.74% respectively compared with that of the Gait Flow Image (GFI). The proposed method has high recognition accuracy, strong real-time and the robustness to view changes.