2026-06-27T16:27:01Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/141902024-11-26T14:55:06Zcom_20.500.14352_14col_20.500.14352_20

Flores Vidal, Pablo Arcadio Gómez González, Daniel Castro Cantalejo, Javier Villarino, Guillermo Montero De Juan, Francisco Javier 2023-06-17T14:22:39Z 2023-06-17T14:22:39Z 2019-08 Flores, P., Gomez, D., Castro, J., Villarino, G., Montero, J.: A new approach to Color Edge Detection. En: Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019). Atlantis Press, Prague, Czech Republic (2019) 10.2991/eusflat-19.2019.53 https://hdl.handle.net/20.500.14352/14190 https://doi.org/10.2991/eusflat-19.2019.53 https://www.atlantis-press.com/proceedings/eusflat-19/125914823 Most edge detection algorithms deal only with grayscale images, and the way of adapting them to use with RGB images is an open problem. In this work, we explore different ways of aggregating the color information of a RGB image for edges extraction, and this is made by means of well-known edge detection algorithms. In this research, it is been used the set of images from Berkeley. In order to evaluate the algorithm’s performance, F measure is computed. The way that color information -the different channels- is aggregated is proved to be relevant for the edge detection task. Moreover, post-aggregation of channels performed significatively better than the classic approach (pre-aggregation of channels). eng https://creativecommons.org/licenses/by-nc/3.0/es/ open access Atribución-NoComercial 3.0 España A new approach to Color Edge Detection conference paper