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Texture Feature Extraction of RGB, HSV, YIQ and Dithered Images using Wavelet and DCT Decomposition Techniques
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 73 - Number 10 |
| Year of Publication: 2013 |
| Authors: Manisha Lumb, Poonam Sethi |
10.5120/12781-9436
|
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
Abstract
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.
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