CODEWITHSUNDEEP
opencvopencv3.0image-segmentationsemantic-segmentationdeeplab
n00b
n00b

Reputation: 1639

Refine segmentation mask based on contours of image

I have an image for which I have the green border as the segmentation mask's outline. I'm looking to refine this outline based on contours found on the original image, to get a mask like the in 2nd image - where the edges of the hair are more refined.

segmentation mask outline enter image description here

I've tried combinations of dilation & erosion of the segmentation mask, but it didn't feel like a generic solution - since it involves manually tuning the kernel size.

Are there better approaches?

Upvotes: 0

Views: 959

Answers (1)

SKG
SKG

Reputation: 163

There is no generic solution. Parameter tuning is always required to get the desired output. For getting more refined fine edges of the hairs, you can apply thresholding as below:

import cv2 as cv
from matplotlib import pyplot as plt

im = cv2.imread("model.jpg",0)
plt.imshow(im)
thresh = cv2.adaptiveThreshold(im,255,cv2.ADAPTIVE_THRESH_MEAN_C,\
            cv2.THRESH_BINARY_INV,31,3)
plt.imshow(thresh)

input: enter image description here

output: enter image description here

Note: The color changes are due to 'matplotlib'.

Upvotes: 1

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