NDLI: Performance evaluation of Local Binary Patterns and it's derivatives for face recognition

Content Provider	IEEE Xplore Digital Library
Author	Meena, K. Suruliandi, A.
Copyright Year	2011
Description	Author affiliation: Computer Science & Engg, Sardar Raja College of Engineering, Tirunelveli, India (Meena, K.) \|\| Dept of Computer Science & Engg, Manonmaniam Sundaranar University, Tirunelveli, India (Suruliandi, A.)
Abstract	Face recognition is a challenging problem in computer vision and human computer interaction. Texture is the surface property which is used to identify and recognize objects in an image. Texture based facial recognition is a fast growing research area in recent years. The LBP method is based on characterizing the local image texture by local texture patterns. In this paper texture based face recognition is investigated by Local Binary Pattern (LBP) and its derivatives Dominant Local Binary Pattern (DLBP), Local Derivative Pattern (LDP) and Advanced Local Binary Pattern (ALBP). Facial features are extracted and compared using K nearest neighbor classification algorithm. G-statistics distance measure is used for classification. Experiments were carried out on JAFFE female and Yale face databases. The results show that LDP consistently perform much better than the remaining methods.
Starting Page	742
Ending Page	746
File Size	1208792
Page Count	5
File Format	PDF
ISBN	9781424479238
e-ISBN	9781424479269
DOI	10.1109/ICETECT.2011.5760216
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-03-23
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Face recognitoin Histograms Local Binary pattern (LBP) Dominant Local Binary Pattern (DLBP) Databases Local Derivative Pattern (LDP) Face recognition Advanced Local Binary Pattern (ALBP) Feature extraction Face Pixel
Content Type	Text
Resource Type	Article

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