2026-08-01T08:50:00Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/720362024-11-25T17:20:03Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense
author
Flores Vidal, Pablo Arcadio
author
Gómez González, Daniel
author
Castro Cantalejo, Javier
author
Montero De Juan, Francisco Javier
2023-06-22T11:02:28Z
2023-06-22T11:02:28Z
2022-09-16
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
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.
eng
Atribución 3.0 España
New Aggregation Approaches with HSV to Color Edge Detection
journal article
URL
https://docta.ucm.es/bitstreams/4be4cff8-4738-4193-a75b-63c6b7d378e0/download
File
MD5
2aacbae22b24fa15bac000e9bd80de88
4436155
application/pdf
montero-aggregation.pdf