Use OpenCV to match features between two images

matcher.py

import numpy
import cv2


original = "original.tif"
cropped = "cropped.jpeg"

def matcher():
  
  # Open images as grayscale
  im1 = cv2.imread(original, cv2.CV_LOAD_IMAGE_GRAYSCALE)
  im2 = cv2.imread(cropped, cv2.CV_LOAD_IMAGE_GRAYSCALE)
  
  # Create feature detector
  fd = cv2.FeatureDetector_create('SURF')
  detector = cv2.GridAdaptedFeatureDetector(fd, 500)
  
  # Detect features on input images
  keypoints1 = detector.detect(im1)
  keypoints2 = detector.detect(im2)
  
  # Create a descriptor extractor
  extractor = cv2.DescriptorExtractor_create('SURF')
  
  # Calculate descriptors
  descriptor1 = extractor.compute(im1, keypoints1)
  descriptor2 = extractor.compute(im2, keypoints2)
  
  # Match descriptor vectors using FLANN match
  FLANN_INDEX_KDTREE = 1
  flann_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)
  
  matcher = cv2.FlannBasedMatcher(flann_params, {})
  matches = matcher.match(descriptor1[1], descriptor2[1])
  for match in matches:
    distance = match.distance
    if distance < 0.2:
      print distance


if __name__ == '__main__':
matcher()