Marco Detchart, CedricLópez Molina, CarlosFernández Fernández, Francisco JavierPagola Barrio, MiguelBustince Sola, Humberto2020-04-172020-04-172018978-3-319-91473-210.1007/978-3-319-91473-2_23https://academica-e.unavarra.es/handle/2454/36747Edge detection is a basic technique used as a preliminary step for, e.g., object extraction and recognition in image processing. Many of the methods for edge detection can be fit in the breakdown structure by Bezdek, in which one of the key parts is feature extraction. This work presents a method to extract edge features from a grayscale image using the so-called ordered directionally monotone functions. For this purpose we introduce some concepts about directional monotonicity and present two construction methods for feature extraction operators. The proposed technique is competitive with the existing methods in the literature. Furthermore, if we combine the features obtained by different methods using penalty functions, the results are equal or better results than stateof-the-art methods.12 p.application/pdfeng© Springer International Publishing AG, part of Springer Nature 2018Edge detectionFeature extractionOrdered directionally monotone functionsPenalty functionsinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess