Abstract
Image processing represents an important challenge in different fields, especially in biomedical field. Mathematical Morphology uses concepts from set theory, geometry, algebra and topology to analyze the geometrical structure of an image. In addition, it is possible to consider methods where the starting point to analyze an image is a fuzzy relation. This paper studies three methods to image edge detection based on a construction method for interval-valued fuzzy relations which can be understood as a gradient from a morphological point of view. The performance of the proposal in detecting medical image edges is tested, showing the method performing better with regard to a least squared adjust.
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Acknowledgments
This work has been partially supported by MEC and FEDER Grant TEC2012-38142-C04-04 and by ERASMUS Mundus Project EUREKA SD 2013-2591.
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Bouchet, A., Quirós, P., Alonso, P., Díaz, I., Montes, S. (2015). Medical Edge Detection Combining Fuzzy Mathematical Morphology with Interval-Valued Relations. In: Herrero, Á., Sedano, J., Baruque, B., Quintián, H., Corchado, E. (eds) 10th International Conference on Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing, vol 368. Springer, Cham. https://doi.org/10.1007/978-3-319-19719-7_20
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DOI: https://doi.org/10.1007/978-3-319-19719-7_20
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