hi i have extracted the feature of the 1000 images by using color Correlogram & saved it in a .mat file, now i want to match some query image(consist of .mat file) with this data base by using Euclidean distance for image retrieval.but i don't know how to find the Euclidean distance between 1000 data base images & one query image. thanks
Dear what is the size of your feature vector, if it is column vector then let say your have 1000 feature vector of 1000 images. I denote it by D, where each column is feature vector of each image, in short column represent single image. and your Query image is Q is single column vector.
it can be computed as simple as;
Q= repmat(Q,1,size(D,2)); E_distance = sqrt(sum((Q-D).^2));
now E_distance is euclidean matrix distance. where each cell is distance of Query with database image.
How did you concatenate data from multiple matfiles into one? I have done it fr only 2 .mat files, but i am stuck in the logic for multiple .mat files. Could you please help me out with the logic?
I have a data set of 160 images, and i extracted features of these images and saved them in .mat file, now i want to match between features of another image and all features that i saved in the .mat file. How i can do this using eulidean distance algorithm?
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