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New Aggregation Approaches with HSV to Color Edge Detection



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Flores Vidal, Pablo Arcadio and Gómez González, Daniel and Castro Cantalejo, Javier and Montero, Javier (2022) New Aggregation Approaches with HSV to Color Edge Detection. International Journal of Computational Intelligence Systems, 15 . ISSN 1875-6891

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Official URL: 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.

Item Type:Article
Uncontrolled Keywords:Color edge detection; HSV; Hexcone model; RGB; Pre-aggregation; Post-aggregation
Subjects:Sciences > Mathematics > Operations research
ID Code:74721
Deposited On:23 Sep 2022 08:27
Last Modified:23 Sep 2022 11:19

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