Neuro-inspired edge feature fusion using Choquet integrals

It 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 f...

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Bibliographic Details
Published in:Information sciences 2021-12, Vol.581, p.740-754
Main Authors: Marco-Detchart, Cedric, Lucca, Giancarlo, Lopez-Molina, Carlos, De Miguel, Laura, Pereira Dimuro, Graçaliz, Bustince, Humberto
Format: Article
Language:English
Subjects:
[formula omitted]-integral
Choquet integral
Edge detection
Feature extraction
Image processing
Re-aggregation functions
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Summary:It 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.
ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2021.10.016