Abstract
Image retrieval method utilizing texture information which is derived from Discrete Wavelet Transformation: DWT together with color information is proposed. One of the specific features of the texture information extracted from portions of image is based on Dyadic wavelet transformation with forming texture feature vector by using energy derived from Gabor transform on 7 by 7 pixel neighbor of significant points. Using the Wang`s dataset, the proposed method is evaluated with retrieval success rate (precision and recall) as well as Euclidian distance between the image in concern (Query image) and the other images in the database of interest and is compared to the other method. As the result through the experiments, it is found that the DWT derived texture information is significantly effective in comparison to the color information.
Highlights
Henning Muller, et al presented the paper which is entitled “Benchmarking image retrieval applications” [1]
The proposed method achieved the improvements of 12%, 17%, 11%, in comparison to the Firm, Simplicity, and Color Salient Points, respectively
It may concluded that the followings, 1) Texture information is greater than color information, 2) Texture information can be extracted with Dyadic wavelet transformation much effectively than the conventional DWT 3) Forming texture feature vector by using energy derived from Gabor transform on 7 by 7 pixel neighbor of significant points is effective for texture information extractions
Summary
Henning Muller, et al presented the paper which is entitled “Benchmarking image retrieval applications” [1]. One of the conclusions is Content Based Image Retrieval: CBIR is the most effective. CBIR based image retrievals is objectively in comparison to the conventional image retrieval methods [3]. The image size of frequency components derived from the conventional DWT is decimated with the factor of 2 by 2, a Dyadic wavelet transformation maintains the image size of frequency component which represent texture information. This paper proposes a method for texture information extraction based on the Dyadic wavelet transformation. Color and texture information is explained followed by the proposed method for image retrieval. The texture information extraction method with Dyadic wavelet transformation is proposed followed by experimental results.
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More From: International Journal of Advanced Research in Artificial Intelligence
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