DocumentCode :
2576454
Title :
Improvement of Texture Image Retrieval Algorithm Based on Sparse Coding
Author :
Yang, Yansi ; Yang, Yingyun ; Zeng, Xuan
Author_Institution :
Inf. Eng. Sch., Commun. Univ. of China, Beijing, China
fYear :
2012
fDate :
10-12 Oct. 2012
Firstpage :
501
Lastpage :
506
Abstract :
The demerits of the texture image retrieval algorithm based on sparse coding are found expression in the low recall and inconspicuous serial priority of qualified images. Several methods are presented in this paper to improve the performance of the image retrieval algorithm. Firstly, Brodatz texture image filter basis function is used for processing the texture images, thereafter, the kurtosis is added to generate the eigenvector, finally, the joint-scale filter basis is utilized to advance the filter effect. Experimental results indicate that the performance of the proposed methods is positive.
Keywords :
eigenvalues and eigenfunctions; filtering theory; image coding; image retrieval; image texture; Brodatz texture image filter basis function; eigenvector; image retrieval algorithm improvement; inconspicuous serial priority; joint-scale filter basis; kurtosis; low recall; sparse coding; Filtering algorithms; Filtering theory; Hidden Markov models; Image coding; Image retrieval; Libraries; Mathematical model; Feature Extraction; Image Retrieval; Natural Images; Sparse Coding Theory of Visual Perception; Texture Image;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2012 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4673-2624-7
Type :
conf
DOI :
10.1109/CyberC.2012.92
Filename :
6385019
Link To Document :
بازگشت