Face recognition, that has a lot of applications in modern life, is still an attractive research for pattern recognition community. Due to the similarity of human faces, face recognition presents a significant challenge for pattern recognition researchers. Hausdorff distance is an efficient parameter for measuring the similarity between objects. Line Hausdorff distance (LHD) technique, which is the applying of Hausdorff distance for face recognition, gives high accuracy in comparing with common methods for face recognition. For fast screen techniques such as LHD, the computational cost is a key issue. A modified Line Hausdorff distance (MLHD) is proposed in this paper. The performance of the proposed method is compared with LHD method for face recognition in various conditions: 1) ideal condition of face, 2) varying lighting conditions, 3) varying poses and 4) varying face expression. It is very encouraging that the proposed method gives lower computational cost than LHD while keeping the accuracy of face recognition equal to the LHD method.

Face recognition, that has a lot of applications in modern life, is still an attractive research for pattern recognition community. Due to the similarity of human face, face recognition presents a significant chalenge for pattern recognition researchers. Modified Hausdorff distance (MHD) is a low computational cost while giving high accuracy for face recognition. In this paper, a modification of MHD (MMHD) is proposed. By applying the ratio of high confident into the calculation of the distance between images, the MMHD gives higher accuracy in face recognition in comparing with MHD method. The MMHD method also gives higher performance than MHD method in face recognition in various non-ideal conditions of image: 1) varying lighting conditions, 2) varying face expressions and 3) varying of poses.