Space and Contourlet Domains Texture Image Retrieval Algorithm
Xinwu Chen, Jingjing Xue, Li Zhang, Shuangbo Xie, Peng Wang
Available Online June 2017.
- https://doi.org/10.2991/icmia-17.2017.72How to use a DOI?
- texture image retrieval; contourlet transform; standard deviation; L1-energy; L2-energy; local oriented statistics information booster.
- Contourlet transform has been widely used in many image processing applications including digital image denoising, texture image retrieval, etc. When contourlet transform is used for texture image retrieval problems, features like standard deviation, skewness, kurtosis, L1-energy, L2-energy and others of contourlet subbands was used to characterize the nature of textures in digital images. Many other methods like local binary patterns are often used to construct texture image retrieval systems. In this work, we combine features from traditional approaches with local oriented statistics information booster (LOSIB) to improve the texture image retrieval rates. Experiments on Brodatz texture image database was carried out, and the results show that the combination of the features from contourlet and space domains can improve the results efficiently.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xinwu Chen AU - Jingjing Xue AU - Li Zhang AU - Shuangbo Xie AU - Peng Wang PY - 2017/06 DA - 2017/06 TI - Space and Contourlet Domains Texture Image Retrieval Algorithm BT - 2017 6th International Conference on Measurement, Instrumentation and Automation (ICMIA 2017) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/icmia-17.2017.72 DO - https://doi.org/10.2991/icmia-17.2017.72 ID - Chen2017/06 ER -