Marco Detchart, CedricLucca, GiancarloLópez Molina, CarlosMiguel Turullols, Laura dePereira Dimuro, GraçalizBustince Sola, Humberto2022-04-122022-04-1220210020-025510.1016/j.ins.2021.10.016https://academica-e.unavarra.es/handle/2454/42714It is known that the human visual system performs a hierarchical information process in which early vision cues (or primitives) are fused in the visual cortex to compose complex shapes and descriptors. While different aspects of the process have been extensively studied, such as lens adaptation or feature detection, some other aspects, such as feature fusion, have been mostly left aside. In this work, we elaborate on the fusion of early vision primitives using generalizations of the Choquet integral, and novel aggregation operators that have been extensively studied in recent years. We propose to use generalizations of the Choquet integral to sensibly fuse elementary edge cues, in an attempt to model the behaviour of neurons in the early visual cortex. Our proposal leads to a fully-framed edge detection algorithm whose performance is put to the test in state-of-the-art edge detection datasets.18 p.application/pdfeng© 2021 The Authors. Creative Commons Attribution 4.0 InternationalCF-integralChoquet integralEdge detectionFeature extractionImage processingRe-aggregation functionsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccess