ABSTRACT
Since the last decade, Content-based Image retrieval
was a hot topic research. The computational complexity
and the retrieval accuracy are the main problems that
CBIR system have to avoid. In this study the method was
proposed to overcome these problems by using the combine
of color moment and texture features. The color feature
was extracted by color moment where the images will be
in the HSV color space. The textures features extracted by
applying Gabor function where the images will be in
grayscale. The similarity measure in this study was
calculated by used Euclidian distance.
The experiments results show that using both color and
texture features to describe the image and use them for
image retrieval is more accurate than using one of them
only.
ALHASSAN, A (2021). Color And Texture Fusion Based Method For Content Based Image Retrieval. Afribary. Retrieved from https://tracking.afribary.com/works/color-and-texture-fusion-based-method-for-content-based-image-retrieval
ALHASSAN, ABDOLRAHEEM "Color And Texture Fusion Based Method For Content Based Image Retrieval" Afribary. Afribary, 19 May. 2021, https://tracking.afribary.com/works/color-and-texture-fusion-based-method-for-content-based-image-retrieval. Accessed 24 Nov. 2024.
ALHASSAN, ABDOLRAHEEM . "Color And Texture Fusion Based Method For Content Based Image Retrieval". Afribary, Afribary, 19 May. 2021. Web. 24 Nov. 2024. < https://tracking.afribary.com/works/color-and-texture-fusion-based-method-for-content-based-image-retrieval >.
ALHASSAN, ABDOLRAHEEM . "Color And Texture Fusion Based Method For Content Based Image Retrieval" Afribary (2021). Accessed November 24, 2024. https://tracking.afribary.com/works/color-and-texture-fusion-based-method-for-content-based-image-retrieval