CODEWITHSUNDEEP
python-2.7opencvimage-processing
user3778289
user3778289

Reputation: 323

How to remove elongated structures(contours) from the binary image

enter image description here
I am trying to remove elongated contours from my binary image but I am still getting most of them. I have tried to remove them using but considering compactness and eccentricity factors but that didn't work in my case.

im=cv2.imread('thresh.png')
gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
cv2.imshow('thres',gray)
gray2 = gray.copy()
mask = np.zeros(gray.shape,np.uint8)
contours, hier = cv2.findContours(gray2,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
  area=cv2.contourArea(cnt)
  if area>=5:
    ellipse = cv2.fitEllipse(cnt)
        # center, axis_length and orientation of ellipse
        (center,axes,orientation) = ellipse

        # length of MAJOR and minor axis
        majoraxis_length = max(axes)
        minoraxis_length = min(axes)
        eccentricity = np.sqrt(1-(minoraxis_length/majoraxis_length)**2)
        #############compactness################
    area=cv2.contourArea(cnt)
    equi_diameter = np.sqrt(4*area/np.pi)
    compactness=equi_diameter/majoraxis_length

        ########################################
        if(eccentricity<=0.6 or eccentricity >1) or (compactness <0.8):
           cv2.drawContours(gray2,[cnt],0,(0,0,0),1)
           cv2.drawContours(mask,[cnt],0,255,-1)

cv2.imshow('final',mask)

Can anyone suggest me some method for removing these elongated contours.

Upvotes: 0

Views: 751

Answers (1)

shoham
shoham

Reputation: 281

One option i can think of, is to calculate each object area and max length, than set a threshold to area/length.

Upvotes: 1

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