Fovea localization in retinal images using spatial color histograms
Date
2023Abstract
The automatic location of the fovea is very useful for diagnosing retinal diseases. It is
a complex problem for which diferent solutions have been proposed based on classical
image processing and Deep Learning techniques. The method presented in this paper is
based on histograms that combine spatial and color information in such a way that the
spatial coordinates are incorporated into conventional color histograms as an additional
dimension. The binarization of these histograms retains a considerable amount of relevant
information from the original image, allowing them to be processed as if they were ordinary images. This approach to the problem results in a simple, fast and efective method for
locating the fovea. Diferent experiments have been carried out with three popular sets of
images: Messidor, REFUGE1 and DIARETDB1, and a comparison was made with other
state-of-the-art techniques. Our results show that the proposed method, despite its simplicity, is capable of surpassing many of these techniques.