International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 73 - Issue 10 |
Published: July 2013 |
Authors: Manisha Lumb, Poonam Sethi |
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Manisha Lumb, Poonam Sethi . Texture Feature Extraction of RGB, HSV, YIQ and Dithered Images using Wavelet and DCT Decomposition Techniques. International Journal of Computer Applications. 73, 10 (July 2013), 41-49. DOI=10.5120/12781-9436
@article{ 10.5120/12781-9436, author = { Manisha Lumb,Poonam Sethi }, title = { Texture Feature Extraction of RGB, HSV, YIQ and Dithered Images using Wavelet and DCT Decomposition Techniques }, journal = { International Journal of Computer Applications }, year = { 2013 }, volume = { 73 }, number = { 10 }, pages = { 41-49 }, doi = { 10.5120/12781-9436 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2013 %A Manisha Lumb %A Poonam Sethi %T Texture Feature Extraction of RGB, HSV, YIQ and Dithered Images using Wavelet and DCT Decomposition Techniques%T %J International Journal of Computer Applications %V 73 %N 10 %P 41-49 %R 10.5120/12781-9436 %I Foundation of Computer Science (FCS), NY, USA
An image can be retrieved from number of features contained in it. But it depends upon its format, which features are best selected for the proper retrieval. In this paper, the RGB, HSV, YIQ and dithered images are retrieved using two computational retrieval techniques; DCT and Wavelet decomposition. When used DCT transformation technique, only HSV images are giving the best results, while when Wavelet transformation is used, the HSV, Dithered and YIQ images are giving satisfactory results, out of which from the accuracy point of view, HSV images are having maximum degree of accuracy in correct retrieval. After analysis, it is found that in DCT as well as in Wavelet decomposition techniques, the HSV images are correctly retrieved.