Abstract
In this paper we present an artificial cortical network, inspired by the Human Visual System (HVS), which extracts the salient contours in color images. Similarly to the primary visual cortex, the network consists of orientation hypercolumns. Lateral connections between the hypercolumns are modeled by a new connection pattern based on co-exponentiality. The initial color edges of the image are extracted in a way inspired by the double-opponent cells of the HVS. These edges are inputs to the network, which outputs the salient contours based on the local interactions between the hypercolumns. The proposed network was tested on real color images and displayed promising performance, with execution times small enough even for a conventional personal computer.
This research was funded by the project PENED 2003 – KE 1354.
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Vonikakis, V., Andreadis, I., Gasteratos, A. (2006). Extraction of Salient Contours in Color Images. In: Antoniou, G., Potamias, G., Spyropoulos, C., Plexousakis, D. (eds) Advances in Artificial Intelligence. SETN 2006. Lecture Notes in Computer Science(), vol 3955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752912_40
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DOI: https://doi.org/10.1007/11752912_40
Publisher Name: Springer, Berlin, Heidelberg
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