Area of multiple blobs in a binary image python

Question

noob here.

I have a (kind of) binary image that contains a known number of blobs that vary in shape and size. The pixel values in each blob equivalent to the blob index. I would like to process (using moments) only the largest 5 blobs.

At the moment I am iterating through every connected pixel incrementing a variable to get the area of each blob (see code below). I then process only the largest blobs as required, however this pixel iteration method is very slow in python.

 for i in range(1, objectCount):
            zm=0.0
            for h in range(im.height):
                for w in range(im.width):
                    pixVal = cv.Get2D(im, h, w)
                    if (pixVal[0] == i):
                        zm=zm+1
            objectArea.append([int(zm)])

Is there a faster way to do this?

Answer 1

Here's the code to replace the above:

hist = cv.CreateHist([255], cv.CV_HIST_ARRAY, [[0,255]], 1)
cv.CalcHist([im] , hist)          
for h in range(255):
    zm = cv.QueryHistValue_1D(hist, h)
    objectArea.append([int(zm)])