DocumentCode :
2867850
Title :
Image Retrieval Based on PCA-LPP
Author :
Zhang, Zhenhua ; Zhu, Xinzhong ; Zhao, Jianmin ; Xu, Huiying
Author_Institution :
Coll. of Math., Phys. & Inf. Eng., Zhej iang Normal Univ. Jinhua, Jinhua, China
fYear :
2011
fDate :
14-17 Oct. 2011
Firstpage :
230
Lastpage :
233
Abstract :
In many areas of image retrieval, pattern recognition and data mining, one is ofen confronted with some form of dimensionality reduction. In this paper, we introduce a algorithm of Principal Components Analysis-Locality Preserving Projections ( PCA-LPP ). This algorithm can compute the principal components of a sequence of data set and at the time optimally preserves the neighborhood structure of the data set. This procedure is done by merging the runs of two algorithms based on principal component analysis (PCA) and Locality Preserving projections (LPP) running sequentially. This algorithm is applied to image retrieval problem. Simulation results on Corel image database showed better accuracy rate of this algorithm compared to PCA and LPP algorithms.
Keywords :
data mining; image retrieval; principal component analysis; Corel image database; PCA-LPP algorithm; data mining; dimensionality reduction; image retrieval; locality preserving projections; pattern recognition; principal component analysis; Algorithm design and analysis; Covariance matrix; Eigenvalues and eigenfunctions; Image retrieval; Principal component analysis; Semantics; Vectors; Locality Preserving Projections; Principal Components Analysis; dimension reduction; image retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Distributed Computing and Applications to Business, Engineering and Science (DCABES), 2011 Tenth International Symposium on
Conference_Location :
Wuxi
Print_ISBN :
978-1-4577-0327-0
Type :
conf
DOI :
10.1109/DCABES.2011.52
Filename :
6119018
Link To Document :
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