Algorithm:
1. Start
2. Read input image, I
3. Resize the input image I, by a scale of 0.15 to get the
resized image Iresized.
4. Apply Otsu segmentation [14] to the image, Iresized.
5. Calculate area of every region in the threshold image,
Iotsu.
6. Select the region with maximum area as the ROI.
7. Calculate its inclination.
8. Correct the inclination of the bone using the formula
8.1. If the bone is inclined to the right, then it is rotated
in anti-clockwise direction by an angle equal to
“90-angle” (i.e. Anglecorrected = 90 - Angleoriginal)
8.2. But if the bone is inclined to the left, then it is
rotated in clockwise direction by an angle equal to
“-90-angle” (i.e. Anglecorrected = - 90 -
Angleoriginal). Here the value obtained will be
negative. This denotes that the image should be
rotated in clockwise direction.
9. The new image obtained is Irot. Next, the co-ordinates of
the bounding box of the maximum area region in the
above image are obtained.
10. Using these coordinates a rectangle containing the bone
region (ROI) is cropped from the image Irot. The new
image obtained is Icrop, which is the final pre-processed
image Inew.
11. Stop
I=imread('12493.png');
J = imresize(I, 0.5);
imshow(J);
level = graythresh(J);
BW = imbinarize(J,level);
imshowpair(J,BW,'montage')
blobMeasurements = regionprops(BW, 'area');
allAreas = [blobMeasurements.Area];
[sortedAreas, sortIndexes] = sort(allAreas, 'descend');
numberToExtract=1;
biggestBlob = ismember(BW, sortIndexes(1:numberToExtract));
imshow(biggestBlob);
stats = regionprops(BW,'Orientation');
Angleoriginal=stats(1).Orientation;
if Angleoriginal<90
Anglecorrected = 90 - Angleoriginal;
else
Anglecorrected = -90 - Angleoriginal;
end
I_rot = ismember(biggestBlob, Anglecorrected);
imshow(I_rot);
