Open AccessA modification of line Hausdorff distance for face recognition to reduce computational cost
Author(s) -
Chau Nguyen Dang,
Tuan Hong
Publication year - 2017
Publication title -
khoa học công nghệ
Language(s) - English
Resource type - Journals
ISSN - 1859-0128
DOI - 10.32508/stdj.v20ik3.1106
Subject(s) - hausdorff distance , facial recognition system , face (sociological concept) , artificial intelligence , computer science , hausdorff space , similarity (geometry) , three dimensional face recognition , pattern recognition (psychology) , line (geometry) , line segment , computer vision , mathematics , face detection , image (mathematics) , geometry , discrete mathematics , social science , sociology
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.