The purpose of interior orientation is to transform the ground coordinate system into a photographic coordinate system (reconstructing the internal geometry of the camera). This transformation is a two-dimensional to two-dimensional change, so we use the aforementioned transformations for this purpose. To perform this transformation and Obtain the conversion parameters requires control points such as control fiducial points.
Then we need checkpoints to check the correctness and accuracy of the calculated parameters. Some of our control points will play a role in this action for us. The image coordinates of these points are provided with high accuracy by the camera manufacturer.
In this project, I’ve written a Python code that can transform the coordinate of a chosen point from an aerial image to its ground coordinates using Affine, Conformal, Projective, and Polynomial transform.
The pictures we used to capture the point are as follows:
The source code and data for the project is available via the following link: