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Research on similarity measurement for texture image retrieval
- Source :
- PLoS ONE, Vol 7, Iss 9, p e45302 (2012), PLoS ONE
- Publication Year :
- 2012
- Publisher :
- Public Library of Science (PLoS), 2012.
-
Abstract
- A complete texture image retrieval system includes two techniques: texture feature extraction and similarity measurement. Specifically, similarity measurement is a key problem for texture image retrieval study. In this paper, we present an effective similarity measurement formula. The MIT vision texture database, the Brodatz texture database, and the Outex texture database were used to verify the retrieval performance of the proposed similarity measurement method. Dual-tree complex wavelet transform and nonsubsampled contourlet transform were used to extract texture features. Experimental results show that the proposed similarity measurement method achieves better retrieval performance than some existing similarity measurement methods.
- Subjects :
- Texture compression
Databases, Factual
Image Processing
Wavelet Analysis
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Information Storage and Retrieval
lcsh:Medicine
Texture (geology)
Pattern Recognition, Automated
Databases
Engineering
Image texture
Similarity (network science)
Artificial Intelligence
Image Interpretation, Computer-Assisted
Computer Simulation
Statistical Methods
Complex wavelet transform
lcsh:Science
Image retrieval
Physics
Multidisciplinary
business.industry
Applied Mathematics
Statistics
lcsh:R
Wavelet transform
Pattern recognition
Image Enhancement
Contourlet
Computer Science
Signal Processing
lcsh:Q
Artificial intelligence
Information Technology
business
Algorithms
Mathematics
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 7
- Issue :
- 9
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....8d5530b1a5916d7d34cbafed1f1a5890