RT info:eu-repo/semantics/article T1 Fovea localization in retinal images using spatial color histograms A1 Sigut Saavedra, José Francisco A1 Núñez,· Omar A1 Fumero Batista, Francisco José A1 Alayón Miranda, Silvia A1 Díaz Alemán, Tinguaro A2 Ingeniería Informática y de Sistemas A2 GAIM (Grupo de Análisis de Imágenes Médicas) K1 Retinal diseases diagnosis K1 Fovea localization K1 Spatial color histogram AB The automatic location of the fovea is very useful for diagnosing retinal diseases. It isa complex problem for which diferent solutions have been proposed based on classicalimage processing and Deep Learning techniques. The method presented in this paper isbased on histograms that combine spatial and color information in such a way that thespatial coordinates are incorporated into conventional color histograms as an additionaldimension. The binarization of these histograms retains a considerable amount of relevantinformation 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 forlocating the fovea. Diferent experiments have been carried out with three popular sets ofimages: Messidor, REFUGE1 and DIARETDB1, and a comparison was made with otherstate-of-the-art techniques. Our results show that the proposed method, despite its simplicity, is capable of surpassing many of these techniques. YR 2023 FD 2023 LK http://riull.ull.es/xmlui/handle/915/35089 UL http://riull.ull.es/xmlui/handle/915/35089 LA en NO https://doi.org/10.1007/s11042-023-16244-6 DS Repositorio institucional de la Universidad de La Laguna RD 17-jun-2024