|Table of Contents|

Collaborative representation based classification based on weightedblock-based LBP histogram vector and analytic dictionary(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2019年02期
Page:
170-
Research Field:
Publishing date:

Info

Title:
Collaborative representation based classification based on weightedblock-based LBP histogram vector and analytic dictionary
Author(s):
Chen Youming1Song Xiaoning1Yu Dongjun2
1.School of IoT Engineering,Jiangnan University,Wuxi 214122,China; 2.School of ComputerScience and Engineering,Nanjing University of Science and Technology,Nanjing 210094,China
Keywords:
collaborative representation dictionary learning local binary pattern face classification
PACS:
TP391
DOI:
10.14177/j.cnki.32-1397n.2019.43.02.008
Abstract:
The traditional collaborative representation based classification(CRC)algorithms using original samples directly to construct an untraditional dictionary may get into some troubles including curse of dimensionality,variations in illumination and appearance. In this paper,a new face classification method based on CRC is proposed by using a set of the weighted block-based local binary pattern(LBP)histogram vectors to construct an analytic dictionary. A block weighted method is presented to optimize the texture features extracted from the LBP. Secondly,the samples are projected into a sparse coefficient space,which is constructed by an analytic dictionary model. The final goal is to perform the robust face classification using the proposed hybrid method. Experimental results conducted on the ORL and the LFW face databases demonstrate that the proposed method has the desirable classification performance.

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Last Update: 2019-04-26