In other words, if you pick a feature (say a corner) on one image, the coordinates of the same corner in the other image is very different. In many applications, we have two images of the same scene or the same document, but they are not aligned. What is Image Alignment or Image Registration? If you have not read that post, I recommend you do it because it covers a very cool application involving the history of photography. Previously, we had covered area based image alignment in ECC Image Alignment. A transformation is then calculated based on these matched features that warps one image on to the other. The technique we will use is often called “feature based” image alignment because in this technique a sparse set of features are detected in one image and matched with the features in the other image. We will demonstrate the steps by way of an example in which we will align a photo of a form taken using a mobile phone to a template of the form. We will share code in both C++ and Python. In this post, we will learn how to perform feature-based image alignment using OpenCV.
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