SIFT features extraction from images and send it to CNN or other classifiers
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Good day,
I have been strugling for days with the following code:
- imds = imageDatastore('mydata','IncludeSubfolders',true,'LabelSource','foldernames');
- numImages = numel(imds.Files);
- for i = 1:numImages
- img = readimage(imds,i); img = im2gray(img);
- img = imbinarize(img); % points = detectSIFTFeatures(img);
- hogFeatures(i, :) = extractHOGFeatures(img,'CellSize',cellSize);
- end
........... The above code is part of MATLAB help, and works well for my data that contains arabic alphabets one per image. (sample attached).
. I have little code to convert these features to an .csv file from a code of SVM classifier or a CNN reads features from the .csv file and does the classification.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/912740/image.png)
When I want to do the same for SIFT features, instead of HOG, the code becomes as:
----------------
- imds = imageDatastore('mydata','IncludeSubfolders',true,'LabelSource','foldernames');
- numImages = numel(imds.Files);
- for i = 1:20
- img = readimage(imds,i); img = im2gray(img);
- img = imbinarize(img); points = detectSIFTFeatures(img);
- SiftFeatures (i, :) = extractFeatures(img,locations);
- end
.................................line 6 generates and error that this type of indexing is not allowed in this type of objects.I can see the SiftFeatures object has complex nested list of variables (7 varibales ) of different dimensions and their inner dimension vary with every images.
my questions are:
- How to convert this data in a feature vector to save it as .csv file or any other suitable form a CNN can read it.
- What features I must take (scale, orentation, octave ..... etc) for better classififcation, or I need to pick all of them.
thanks in advance.
Shahid B.
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