2026-08-01T08:50:00Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/720362024-11-25T17:20:03Zcom_20.500.14352_14col_20.500.14352_15

00925njm 22002777a 4500 dc Flores Vidal, Pablo Arcadio author Gómez González, Daniel author Castro Cantalejo, Javier author Montero De Juan, Francisco Javier author 2022-09-16 The 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. Flores-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-x 1875-6891 10.1007/s44196-022-00137-x https://hdl.handle.net/20.500.14352/72036 https://doi.org/10.1007/s44196-022-00137-x New Aggregation Approaches with HSV to Color Edge Detection