Automatic Recognition Method of Surface Defects Based on Gabor Wavelet and Kernel Locality Preserving Projections

2010 ◽  
Vol 36 (3) ◽  
pp. 438-441 ◽  
Author(s):  
Xiu-Yong WU ◽  
Ke XU ◽  
Jin-Wu XU
Keyword(s):  
Surface Defects ◽  
Automatic Recognition ◽  
Gabor Wavelet ◽  
Recognition Method ◽  
Locality Preserving Projections ◽  
Locality Preserving

Gait Recognition Based on Locality Preserving Projections

2015 ◽  
Vol 738-739 ◽  
pp. 625-630
Author(s):  
Chao Li ◽  
Jin Ye Peng ◽  
Jing Guo ◽  
Xian Feng Wang ◽  
Xu Qi Wang
Keyword(s):  
Nearest Neighbor ◽  
Wavelet Packet ◽  
Gait Recognition ◽  
Recognition Method ◽  
The Public ◽  
Nearest Neighbor Classifier ◽  
Locality Preserving Projections ◽  
Locality Preserving ◽  
Neighbor Classifier

A gait recognition method based on wavelet packet decomposition (WPD) and Locality preserving projections (LPP) is proposed in this paper. The method includes the following steps, pretreatment, feature extraction by WPD and dimensionality reduction by LPP and classification of the test samples to a corresponding class according to the nearest neighbor classifier. The experiment results on the public gait database show the effectiveness of the proposed method.

Face recognition algorithm based on Gabor wavelet and locality preserving projections

2017 ◽  
Vol 31 (19-21) ◽  
pp. 1740041 ◽  
Author(s):  
Xiaojie Liu ◽  
Lin Shen ◽  
Honghui Fan
Keyword(s):  
Face Recognition ◽  
Gabor Filter ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Gabor Wavelet ◽  
Light Illumination ◽  
Locality Preserving Projections ◽  
Locality Preserving ◽  
Illumination Changes ◽  
The Face

In order to solve the effects of illumination changes and differences of personal features on the face recognition rate, this paper presents a new face recognition algorithm based on Gabor wavelet and Locality Preserving Projections (LPP). The problem of the Gabor filter banks with high dimensions was solved effectively, and also the shortcoming of the LPP on the light illumination changes was overcome. Firstly, the features of global image information were achieved, which used the good spatial locality and orientation selectivity of Gabor wavelet filters. Then the dimensions were reduced by utilizing the LPP, which well-preserved the local information of the image. The experimental results shown that this algorithm can effectively extract the features relating to facial expressions, attitude and other information. Besides, it can reduce influence of the illumination changes and the differences in personal features effectively, which improves the face recognition rate to 99.2%.

Complete Discriminant Locality Preserving Projections for Face Recognition

2010 ◽  
Vol 21 (6) ◽  
pp. 1277-1286 ◽  
Author(s):  
Li-Ping YANG ◽  
Wei-Guo GONG ◽  
Xiao-Hua GU ◽  
Wei-Hong LI ◽  
Xing DU
Keyword(s):  
Face Recognition ◽  
Locality Preserving Projections ◽  
Locality Preserving
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