Looking at your comments, an appropriate solution would be: A = imread(‘Car.jpg’); % loads the image with a crop tool, select the region to be cropped B = imcrop(A); close % Displays the cropped region figure, imshow(B);
In case of an image with LSB enhancement applied, I cannot think of a way to reverse it back to its original state because there is no clue about the original values of RGBs. They are set to either 255 or 0 depending on their Least Significant Bit. The other option I see round here … Read more
As @neil said there is no simple answer. But I would like to tell you how I would approach this non-trivial task. Get as much data as possible. This is critical to get this task done. If you have small amount of data, higher the chance you would choose parameters that work on the data … Read more
You could do something like this: A = imread (‘tFKeD.jpg’); C=bwlabel(A); IM2 = imcomplement(C); % // invert the image so that your objects are 1 se = strel(‘diamond’,3); % // Create a morphological object BW2 = imdilate(IM2,se); L=bwlabel(BW2); % // Label your objects E = regionprops(L,’area’); % // Get the respective area Area = cell2mat(struct2cell(E)); … Read more
As a basic technique, use binarization and connected component analysis. This will give you “blobs” corresponding to the individual characters and you can get their bounding boxes. You will face extra difficulties: some characters can touch and form a single blob. You will need some detection logics to split them, for instance based on size … Read more