Abstract
Soft morphological filters form a class of filters with many desirable properties. They were introduced to improve the behaviour of standard morphological filters in detail preservation and noise elimination. In this paper, a framework for soft morphological colour image processing using a fuzzy model is introduced. This extends the standard colour morphological operators in the same way that soft greyscale morphology extends the standard greyscale morphology theory. The primary and secondary operations of the new soft morphological approach are defined. The proposed operators are less sensitive to image distortion and to small variations in the shape of the objects, and perform significantly better in impulse noise removal problems, compared to standard morphological operators. Experimental results of the application to real colour images demonstrate these advantageous characteristics of the new operators. Additionally, illustrative examples that exhibit the applicability of the proposed methodology to edge detection problems are also included.
Similar content being viewed by others
Author information
Authors and Affiliations
Corresponding author
Additional information
An erratum to this article can be found at http://dx.doi.org/10.1007/s10044-004-0216-3
Rights and permissions
About this article
Cite this article
Louverdis, G., Andreadis, I. Soft Morphological Filtering Using a Fuzzy Model and its Application to Colour Image Processing. Formal Pattern Analysis & Applications 6, 257–268 (2004). https://doi.org/10.1007/s10044-003-0193-y
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/s10044-003-0193-y