Efficient colour texture image retrieval by combination of colour and texture features in wavelet domain

Recent study [30–35] addressing texture-based image segmentation and classification using very high resolution (VHR) remote sensing images has proved the capacity of the local

Discrimination over the Spectral Power Density The two first experiments were defined to assess the abil- ity of texture features to discriminate textures according to the

Like the continuous variables correspond- ing to the query image visual features, the discrete vari- ables corresponding to the keywords associated to the query images are included

Since the reflec- tion model used for model-based texture methods is just an approximation, there is a difference between the real image and the image rendered by the reflection

Palm and Lehmann (Palm & Lehmann, 2002) show that the Gabor transform is competitive at describing image textures and these texture feature extraction from the color

In this paper, we proposed a new texture feature associated with an adapted similarity measure: the Relocated Colour Contrast Occurrence matrix associated to a

In our case, we obtained for lower than 0.0001 with SVR gaussian kernel, an average PSNR close to 42.38, 46.58, 46.10, 41.29 dB, 49.47 dB and 38.46 dB with bit rate about 0.7

This paper is a study of image retrieval based on color and texture features, the main algorithms include color histogram,color moment,gray level co-occurrence