Extract objects (fingerprint and signature) from an image using OpenCV and python

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At my website I receive an image contains the user fingerprint and signature, I wan't to extract these two pieces of information.

for example: Original Image

import os
import cv2
import numpy as np

def imshow(label, image):
    cv2.imshow(label, image)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

#read image
rgb_img = cv2.imread('path')
rgb_img = cv2.resize(rgb_img, (900, 600))
gray_img = cv2.cvtColor(rgb_img, cv2.COLOR_BGR2GRAY)

Gray Image

#canny edge detection
canny = cv2.Canny(gray_img, 50, 120)

canny edge image 

# Morphology Closing
kernel = np.ones((7, 23), np.uint8)
closing = cv2.morphologyEx(canny, cv2.MORPH_CLOSE, kernel)

Morphology Closing 

# Find contours 
contours, hierarchy = cv2.findContours(closing.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)

# Sort Contors by area and then remove the largest frame contour
n = len(contours) - 1
contours = sorted(contours, key=cv2.contourArea, reverse=False)[:n]

copy = rgb_img.copy()

# Iterate through contours and draw the convex hull
for c in contours:
    if cv2.contourArea(c) < 750:
        continue
    hull = cv2.convexHull(c)
    cv2.drawContours(copy, [hull], 0, (0, 255, 0), 2)
    imshow('Convex Hull', copy)

Image divided to parts

Now my goals are:

  1. Know which part is the signature and which is the fingerprint
  2. Resolve the contours overlapping if exist

P.S: I'm not sure if the previous steps are final so please if you have better steps tell me.

These are some hard examples i may wanna deal with Hard example 1Hard example 2

opencv3.0 computer-vision opencv image-processing matlab
1 Answers

You can use morphology for finger print and signature selecting. By example:

import cv2 
import numpy as np
img = cv2.imread('fhZCs.png')
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
img=cv2.bitwise_not(img) #negate image

#color definition
blue_upper = np.array([130,255,255])
blue_lower = np.array([115,0,0])

#blue color mask (sort of thresholding, actually segmentation)
mask = cv2.inRange(hsv, blue_lower, blue_upper)
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (20,20))
finger=cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)

mask2=cv2.morphologyEx(finger, cv2.MORPH_DILATE, kernel)
signature=cv2.compare(mask2, mask, cv2.CMP_LT)
signature=cv2.morphologyEx(signature, cv2.MORPH_DILATE, kernel)

signature=cv2.bitwise_and(img, img, mask=signature)
signature=cv2.bitwise_not(signature)

finger=cv2.bitwise_and(img, img, mask=finger)
finger=cv2.bitwise_not(finger)

cv2.imwrite('finger.png', finger)
cv2.imwrite('signature.png',signature)

finger print signature

user_132264400
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