Flores Vidal, Pablo ArcadioGómez González, DanielCastro Cantalejo, JavierMontero De Juan, Francisco Javier2023-06-222023-06-222022-09-16Flores-Vidal, P., Gómez, D., Castro, J., Montero, J.: New Aggregation Approaches with HSV to Color Edge Detection. Int J Comput Intell Syst. 15, 78 (2022). https://doi.org/10.1007/s44196-022-00137-x1875-689110.1007/s44196-022-00137-xhttps://hdl.handle.net/20.500.14352/72036The majority of edge detection algorithms only deal with grayscale images, while their use with color images remains an open problem. This paper explores different approaches to aggregate color information of RGB and HSV images for edge extraction purposes through the usage of the Sobel operator and Canny algorithm. This paper makes use of Berkeley’s image data set, and to evaluate the performance of the different aggregations, the F-measure is computed. Higher potential of aggregations with HSV channels than with RGB channels is found. This article also shows that depending on the type of image used, RGB or HSV, some methods are more appropriate than others.engAtribución 3.0 Españahttps://creativecommons.org/licenses/by/3.0/es/New Aggregation Approaches with HSV to Color Edge Detectionjournal articlehttps://doi.org/10.1007/s44196-022-00137-xopen access519.8Color edge detectionHSVHexcone modelRGBPre-aggregationPost-aggregationInvestigación operativa (Matemáticas)1207 Investigación Operativa