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pythonnumpyimage-processingpixelopencv3.0

Calculate minimum distance of point in image mask to a set of points

I have an image mask (differenceM) like this: enter image description here

For every single white pixel (pixel value != 0), I want to calculate the minimum distance from that pixel to a set of points. The set of points are points on the external contour which will be stored as a numpy array of [x_val y_val]. I was thinking of doing this: 

...
def calcMinDist(dilPoints):
    ...

#returns 2d array (same shape as image)
def allMinDistDil(dilMask):
    dilPoints = getPoints(dilMask)
    ...
    return arrayOfMinValues

#more code here

blkImg = np.zeros(maskImage.shape,dtype=np.uint8)
blkImg.fill(0) 

img_out = np.where(differenceM,allMinDistDil(dilatedMask),blkImg)

....

But the problem with this is, in order to calculate minimum distance from a pixel point to a set of points (obtained from getPoints function), I'll need to pass in the pixel point (index?) as well. But (if my understanding is correct,) with this where function, it only checks for true and false values in the first parameter...So the way I wrote the np.where() function won't work.

I've considered using nested for loops for this problem but I'm trying to avoid using for loops because I have a lot of images to process.

May I ask for suggestions to solve this? Any help would be greatly appreciated!

Solution

  • Instead of using the np.where() function to find the specific pixels that are not zero, I applied: 

    diffMaskNewArray = np.transpose(np.nonzero(binaryThreshMask))

    to get the points where the values are not zeros. With this array of points, I iterated through each point in this array and compared it with the array of boundary points of the masks and used:

    shortestDistDil = np.amin(distance.cdist(a, b, 'euclidean'))

    to find the min distance between the point and the set of boundary points.