Hybrid Method for Face Description Using LBP and HOG
AbstractFace recognition has become an important issue in our current life and it is a fundamental task for applications such as face tracking, red – eye removal, face recognition and face expression recognition.
In this paper we present a hybrid approach based on combination of local binary pattern (LBP)and Histogram of Oriented Gradient(HOG). LBP algorithms, which works with the shape and texture information are taken into consideration for representing the facial image. The hog algorithm of descriptor attributes is used to detect the object. It is computed using a dense grid of uniformly spaced cells and uses overlapping local contrast normalization for improved accuracy.
The ORL database was used to test each algorithm for a set of images. The efficiency of the LBP algorithm is evaluated by distinguishing a group of face images from 80%. The HOG algorithm achieved 90% classification accuracy obtained, while the hybrid method 94.25%.
Phillips, P., Grother, P., Micheals, R.J., Blackburn, D.M., Tabassi, E., Bone, J.M.: ‟Face recognition
vendor test 2002 results. Technical” report (2003).
Zhao, W., Chellappa, R., Rosenfeld, A., Phillips, P.J.: ‟Face recognition: a liter- ature survey”.
Technical Report CAR-TR-948, Center for Automation Research, University of Maryland (2002).
Phillips, P.J., Wechsler, H., Huang, J., Rauss, P.: ‟The FERET database and evaluation procedure for
face recognition algorithms”. Image and Vision Computing 16 (1998) 295–306
Ojala, T., Pietik¨ainen, M., Harwood, D.: ‟A comparative study of texture measures with classification
based on feature distributions. Pattern Recognition” 29 (1996) 51–59
Ojala, T., Pietik¨ainen, M., M¨aenp¨a¨ a, T.: ‟ Multiresolution gray-scale and rotation invariant texture
classification with local binary patterns”. IEEE Transactions on Pattern Analysis and Machine
Intelligence 24 (2002) 971–987
Dalal N, Triggs B. ‟Histograms of oriented gradients for human detection”. In: IEEE Conference on
Computer Vision and Pattern Recognition (CVPR). San Diego, CA, USA, 2005, 1: 886-893
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