Well I kind did something like what you are trying to do. I have a lot of images that are very similar so I tried to "search" for then using the following code (I simplify ):
def rmsdiff(im1, im2):
"Calculate the root-mean-square difference between two images"
diff = ImageChops.difference(im1, im2)
h = diff.histogram()
sq = (value*((idx%256)**2) for idx, value in enumerate(h))
sum_of_squares = sum(sq)
rms = math.sqrt(sum_of_squares/float(im1.size * im1.size))
im1 = Image.open(pathOfKnowImage)
folder_img = os.listdir(pathOfUnknowImages)
for arq in folder_img:
im2 = Image.open('pathOfUnknowImages/%s' % arq)
v = rmsdiff(im1,im2)
if v < 0.2:
For my understanding the layout of the resumes would be the same (colors, boxes, font sizes) so using this range 0-0.2 you might find and classify the resumes.
You could take 3 types os resumes and 10 or mores of this resumes in one folder and try the code above, you could move the images to folders and later see if it is working