how do i save extracted feature vectors of an image database?

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nissrine Neyy 2021-1-2

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评论： nissrine Neyy 2021-1-9

Hello everybody

i have a DB of images for a CBIR project and i have to extract different types of features (color : using HSV, texture : using LBP) which i already did, now my qs is how to save those extracted features in a dataset of features to which the CBIR system would go back to, to retreive the similar images ? .. is it a ".mat" file or some other way ? and is it possible to gather the different types of features in the same dataset knoing that their vector sizes are different too? can anyone please help

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Answer 1

Image Analyst 2021-1-2

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在 MATLAB Online 中打开

Yes, you can save your variables in a .mat file. Use the save() function, like

save('answers.mat', 'var1', 'feature2', 'something3');

or whatever. They don't all need to be the same size or even class.

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Image Analyst 2021-1-2

Yes, exactly. You tell save what variables you want to save. Then you use load() to recall them. All the variables you saved will be in a structure. If you want them in their own variable with names like they used to have then you can take the field and put it into a variable like you did.

If you compute the difference between an unknown image, and the features you saved for your training set, then you can do that. I don't know what metrics you want to measure. Of course they may have different units or even be unitless. For example you might store the gray level intensity, the mean and stddev of all the individual color channels, the area fraction of something, etc. So you can't just take the Euclidean distance of all of them because the area fraction will be between 0 and 1 and be unitless while the intensities have much larger ranges and have units of gray levels. So you have to figure out some weighting to apply to the various metrics to get some sort of overall similarity index.

Once you have that, you can pull out image names from your database that have similar metrics as your test image. For example like in this extremely cool, interactive CBIR website that recalls images based on colors you tell it.

https://labs.tineye.com/multicolr/#colors=e72653,445e9a;weights=50,50;

nissrine Neyy 2021-1-3

I appreciate your reponse, and the CBIR website is really cool.

so to answer you, what i want to measure is the HSV and LBP feautures extracted from both the unknown/query image and the database image, i'll use for that the euclidian distance (it could be any other methode euclidian, manhatan distance or mahalanobis ..), i know i can't apply the euclidean distance (for example) on all the metrics just like that, because each would have a distinct specificity to consider (as you gave in the example of intensities and area fraction), and i kind of have the same thing in my case cuz the output feature vector for HSV and LBP are different in size (the HSV gives me a vector of 1x32, and LBP a vector of 1x3776

excuse my question, but the part of pulling out the image names that have similar metrics how does it happen knowing that the distance computing happens only between the query image feature and features of the database images (which are now no longer images with names) ? should we save the features (somehow i don't really know) with the names of images, or do those features stay related to the images and names even if they're now just features (values) stored in their own file (in this case a .mat file) ?

Image Analyst 2021-1-8

Show the whole loop. You left out the parts where you get new baseFileName, HSV_Images, and LBP_Images. If baseFileName changes in the loop (as it should, along with the images), then the structure array should have different file names.

nissrine Neyy 2021-1-9

在 MATLAB Online 中打开

Got it fixed, it's actually silly as an issue, it was just the ':' missing in the :

k = 1:numberOfFiles

Thank you anyway

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