Self-calibration of the Fundus Camera Using the Genetic Algorithm

In this article, we present a method of Self-calibration of the fundus camera from the background images of the eye. The data is limited to inter-view homographys, between a reference image and any images. Our first contribution is to propose a new Self-calibration method of the fundus camera based on the idea of adopting as an estimate of the movement of the camera, the movement associated with the eye. A second contribution is the application of the genetic algorithm to determine the internal parameters of the camera. Our method is robust and gives good results as demonstrated by our experiments.

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