I'm very new to OpenCV and recently, I'm trying to compare two images of rails, one with a train and one without. After the comparison, I apply a threshold, and there are some 'holes' in the white regions which I do not want. Currently, I am using dilation with 4 iterations and kernel set to "None", which defaults to a 3x3 by my understanding.
How do I decide what sort of kernel to use so that the dilation does a better job at making the white region continuous? Would also be nice if I could remove the small white blobs in the background. Here is the code:
resized = imutils.resize(img2, width=1050) resized2 = imutils.resize(img3, width=1050) grayA = cv2.cvtColor(resized, cv2.COLOR_BGR2GRAY) grayB = cv2.cvtColor(resized2, cv2.COLOR_BGR2GRAY) grayA = cv2.GaussianBlur(grayA,(7,7),0) grayB = cv2.GaussianBlur(grayB,(7,7),0) frameDelta = cv2.absdiff(grayA, grayB) thresh = cv2.threshold(frameDelta, 20, 255, cv2.THRESH_BINARY)[1] thresh = cv2.dilate(thresh, None, iterations=4) 
Complete beginner in this, so even general tips/advice to improve these comparisons would be vastly appreciated!
71 Answer
Perhaps this will give you some idea about morphology in Python/OpenCV. First I use a square "open" kernel about the size of the small white spots to remove them. Then I use a horizontal rectangle "close" kernel about the size of the black gap to fill it. "Open" removes white regions (or fills black gaps) and close removes black regions (or fills white gaps)
Input:
import cv2 import numpy as np # read image as grayscale img = cv2.imread('blob3.png', cv2.IMREAD_GRAYSCALE) # threshold to binary thresh = cv2.threshold(img, 0, 255, cv2.THRESH_BINARY)[1] # apply morphology open with square kernel to remove small white spots kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (19,19)) morph1 = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel) # apply morphology close with horizontal rectangle kernel to fill horizontal gap kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (101,1)) morph2 = cv2.morphologyEx(morph1, cv2.MORPH_CLOSE, kernel) # write results cv2.imwrite("blob3_morph1.png", morph1) cv2.imwrite("blob3_morph2.png", morph2) # show results cv2.imshow("thresh", thresh) cv2.imshow("morph1", morph1) cv2.imshow("morph2", morph2) cv2.waitKey(0) Morphology Square Open:
Morphology Rectangle Close:
Alternate Morphology Square Close:
