Huang, Supporting Ranked Boolean Similarity Queries in MARS, IEEE Transaction on Knowledge and Data Engineering, Vol. Michael Ortega, Yong Rui, Kaushik Chakrabarti, Kriengkrai Porkaew, Sharad Mehrotra, and Thomas S. Euclidean distance between ColorMoments of two images can be used to measure the dis-similarity (distance) between two images. the 16 values are: (one for each direction). co-ocurrence in 4 directions is computed (horizontal, vertical, and two diagonal directions). images are converted to 16 gray-scale images. Euclidean distance between Color Moments of two images can be used to represent the dis-similarity (distance) between two images.Ĭo-occurrence Texture: 16 dimensions (4 x 4) the 9 values are: (one for each of H,S, and V in HSV color space)
Histogram Intersection can be used to measure the similarity between two images. 4x2 Color Histogram for each sub-image is computed. each image is divided into 4 sub-images (one horizontal split and one vertical split). Histogram intersection (overlap area between ColorHistograms of two images) can be used to measure the similarity between two images.Ĭolor Histogram Layout: 32 dimensions (4 x 2 x 4 = H x S x sub-images) the value in each dimension in a ColorHistogram of an image is the density of each color in the entire image. HSV color space is divided into 32 subspaces (32 colors : 8 ranges of H and 4 ranges of S). The same image has the same ID in all files but the image ID is not the same as the image filename.įrom each image four sets of features were extracted:Ĭolor Histogram: 32 dimensions (8 x 4 = H x S) The first value in a line is is the image ID and the subsequent values are the feature vector (e.g. For each file, a line corresponds to a single image. There are 68,040 photo images from various categories.Įach set of features is stored in a separate file. The original image collection was obtained from Corel at. Four sets of features are available based on the color histogram, color histogram layout, color moments, and co-occurence
Click here to try out the new site.ĭownload: Data Folder, Data Set DescriptionĪbstract: This dataset contains image features extracted from a Corel image collection. Check out the beta version of the new UCI Machine Learning Repository we are currently testing! Contact us if you have any issues, questions, or concerns.
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