Local Binary Pattern (LBP) feature to face recognition has been gaining interest lately. In this paper, a noval face recognition method based on Local Binary Pattern with Image Euclidean Distance(IMED) was proposed. IMED is first embedded in face images. Then a face image is divided into several blocks (facial regions) from which we extract local binary patterns and construct a global feature histogram that represents both the statistics of the facial micro-patterns and their spatial locations. At last, face recognition is performed using a nearest neighbor classifier in the computed feature space with Chi-Squared as a dissimilarity measure. Experiments show that IMED improve the performance of standard LBP algorithm.