Image Retrieval Using CBIR Including Light Position Analysis
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We propose a method for estimating the weight of the light source position to content-based image retrieval (CBIR) through retrieving image data. The image retrieval method makes use of a multi-dimensional descriptor expressing the features of the image. A multi-directional Gabor filter is then applied in order to extract the contour direction of the image, and a color correlation is applied in order to analyze the distribution of the position between the colors in the image. An HSV histogram and chromatic distribution information were obtained for the color composition analysis, and the light source position in the image was estimated for the main region extraction. The relative similarity between the images was measured through a relative comparison between each descriptor. In conventional image retrieval, there is a disadvantage in terms of the large computational intensity required, because the accuracy is degraded when simple information is used or when the result is estimated through a comparison of complex image components. However, the proposed method adds a light source location analysis element in order to ensure accurate retrieval. Image retrieval using the proposed method achieves an average retrieval accuracy of 85%, indicating that its reliability is superior to that of previously described methods.
KeywordsImage retrieval Color correlogram Color histogram Spatial context Gabor filter
This work was supported by the research grant of the Kongju National University in 2017.
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