I couldn't find a perfect explanation for how getPerspectiveTransform and warpPerspective work in OpenCV, specifically in Python. My understanding of the methods is :
Given 4 points from a source image and 4 new points getPerspectiveTransform returns a (3, 3) matrix that somehow crops the image when sent into warpPerspective as an argument. I thought that the 4 points(from src image) form a polygon on the image which is then removed/cropped and this new cropped image is then fitted between the newly given 4 points and also I saw that warpPerspective takes the input size of the new image. So I inferred this as, if the new points' max-height/max-width(Calculated from the points...imagining the points are corners of a rectangle or a quadrilateral) is less than the provided width or height the remaining area is left blank that is essentially black/white, but this wasn't the case...if the width/height calculated from the new points is less than the provided width and height the remaining space is filled with some part of the source image that is essentially the outer part of the 4 source points...
I wasn't able to comprehend this behavior...
So am I interpreting the methods incorrectly? if so please provide the correct interpretation of these methods.
PS. I'm pretty new to OpenCV and it would be great if someone explains the underlying math that is used by getPerspectiveTransform warpPerspective.
Thanks in advance.
1 Answer
These functions are parts of an image processing concept called Geometric transformations. When taking a picture in real life, there is always some sort of geometric distortion which can be removed using Geometric transformations. It has other applications too, including construction of mosaics, geographical mapping, stereo and video.
Here's an example from this site :
So basically warpPerspective transforms the source image to the desired version of it and it does the job using a 3*3 transformation matrix given by getPerspectiveTransform.
See more details here.
Now if you wonder how to find that pair of 4 dots from source and dest image, you should check another image processing concept called Feature extraction. These are methods that perfectly find important regions of an image and you can match them to another image of the same object taken from a different view. (check SIFT, SURF, ORB ,etc.)
An example of matched features:
So warpPerspective won't just crop your image, it will transfer the whole image (not just the region specified by 4 dots) base on the transformation matrix and those dots will only be used to find the correct matrix.
