RT Journal Article
T1 New Aggregation Approaches with HSV to Color Edge Detection
A1 Flores Vidal, Pablo Arcadio
A1 Gómez González, Daniel
A1 Castro Cantalejo, Javier
A1 Montero De Juan, Francisco Javier
AB 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.
PB Atlantis Press
SN 1875-6891
YR 2022
FD 2022-09-16
LK https://hdl.handle.net/20.500.14352/72036
UL https://hdl.handle.net/20.500.14352/72036
LA eng
NO 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
NO Ministerio de Ciencia, Innovación y Universidades (España)
DS Docta Complutense
RD 17 abr 2025