It is my understanding that you are trying to generate HOG features from a list of images, each with a specified ROI location stored in a Table. The function “extractHOGFeatures()” does not take ROI as arguments directly. However, you can try masking the image using the ROI first, before passing into the “extractHOGFeatures()”. In the code below, 'roiTable' refers to the table name in your workspace with two fields, 'maskLocation' and 'imageLocation'. You can then loop through the table to generate the training data from features.
- If ROIs are stored as black and white image:
for i = 1:numel(roiTable.maskLocation);
roiMask = imread(roiTable.maskLocation(i)); % This should return a 2-D Logical array
% For colored images, convert the mask to a 3-D matrix
roiMask(:,:,2) = roiMask;
roiMask(:,:,3) = roiMask(:,:,1);
% Read the image
img = imread(roiTable.imageLocation(i));
img_new = img;
img_new(roiMask==0) = 0
[featureVector,hogVisualization] = extractHOGFeatures(img_new);
trainingSet(i,:) = featureVector;
- If ROIs are saved as polygonal data, you can create a mask using the function “roipoly(img,c,r)” to generate a mask, where ‘c’ and ‘r’ contains x,y coordinates of polygon vertices respectively.
