Goal: Learn how to implement image alignment

• Align two images by feature matching, find their homography, and warp the transformed image into an aligned image.

Readings and sample codes

• Image Alignment (Feature Based) using OpenCV (C++/Python)

Program and test images

• Prepare two images for one object. One image is aligned image, another one is a transformed image that can be scaled, rotated, translated and perspectively transformed.
• To find the homography between the two images, you need to perform keypoint feature matching.
  • Use at least two keypoint methods.
  • Use at least two feature matching methods.

Web Report

• Create a web page with descriptions, explanation and pictures for your programs.
• Requirements of the report page:
  • For each program code, you have to write 4 parts: (1) goal of this code, (2) theory and principle of the code, (3) code segment explanation, and (4) result comparison or analysis.
  • Use your image to run your programs.
  • Compare and discuss the result images, and explain why the change of methods can produce different results.
  • Conclude with your best results.
• Submit your web address by Google Classroom.