NDLI: A Novel Local Pattern Descriptor—Local Vector Pattern in High-Order Derivative Space for Face Recognition

Content Provider	IEEE Xplore Digital Library
Author	Kuo-Chin Fan Tsung-Yung Hung
Copyright Year	1992
Abstract	In this paper, a novel local pattern descriptor generated by the proposed local vector pattern (LVP) in high-order derivative space is presented for use in face recognition. Based on the vector of each pixel constructed by computing the values between the referenced pixel and the adjacent pixels with diverse distances from different directions, the vector representation of the referenced pixel is generated to provide the 1D structure of micropatterns. With the devise of pairwise direction of vector for each pixel, the LVP reduces the feature length via comparative space transform to encode various spatial surrounding relationships between the referenced pixel and its neighborhood pixels. Besides, the concatenation of LVPs is compacted to produce more distinctive features. To effectively extract more detailed discriminative information in a given subregion, the vector of LVP is refined by varying local derivative directions from the \(n\) th-order LVP in \((n-1)\) th-order derivative space, which is a much more resilient structure of micropatterns than standard local pattern descriptors. The proposed LVP is compared with the existing local pattern descriptors including local binary pattern (LBP), local derivative pattern (LDP), and local tetra pattern (LTrP) to evaluate the performances from input grayscale face images. In addition, extensive experiments conducting on benchmark face image databases, FERET, CAS-PEAL, CMU-PIE, Extended Yale B, and LFW, demonstrate that the proposed LVP in high-order derivative space indeed performs much better than LBP, LDP, and LTrP in face recognition.
Sponsorship	IEEE Signal Processing Society
Page Count	15
File Size	5884213
Starting Page	2877
Ending Page	2891
File Format	PDF
ISSN	10577149
Volume Number	23
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vectors Feature extraction Image coding Face recognition Face Transforms Encoding face recognition Local pattern descriptors local binary pattern (LBP) local derivative pattern (LDP) local tetra pattern (LTrP) local vector pattern (LVP) comparative space transform (CST)
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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