/panorama-stitching

Stitches two or more images to form image panorama.

Primary LanguageJupyter Notebook

panorama-stitching

Portion-Watermarking

Prerequisite

  • Sift and surf cannot be used with new versions of open-cv that is why using orb local invariant descriptor.
  • Orb is based on = FAST keypoint detector and the BRIEF descriptor
  • image
  • (lighter than p, darker than p or similar to p).
  • If more than 8 pixels are darker or brighter than p than it is selected as a keypoint.
  • In brief, each keypoint is described by a feature vector which is 128–512 bits string.
  • image
  • BRIEF is not rotation invariant , so ORB uses rotation aware brief.

Implementation

  • STEP 1 : READ IMAGES AND TRANSFROM THEM TO GRAYSCALE. image

  • STEP 2 : Function to Detect & Describe the Feature Descriptors.

  • STEP 3 : Displaying Keypoints Extracted from the function call of previous step.

image

  • STEP 4 : Create and return a Matcher Object

  • STEP 5 : RAW Matches image

  • STEP 6 : Homography Matrix computation

  • STEP 7 : Panaroma Correction

image

  • STEP 8 : Transform the panorama image to grayscale and threshold it image

😉 Thanks