Agent-based optimal control for image processing

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Authors: Alessio Oliviero, Simone Cacace, Giuseppe Visconti
Cited by: 0
References: 42

Abstract

We investigate the use of multi-agent systems to solve classical image processing tasks, such as colour quantization and segmentation. We frame the task as an optimal control problem, where the objective is to steer the multi-agent dynamics to obtain colour clusters that segment the image. To do so, we balance the total variation of the colour field and fidelity to the original image. The solution is obtained resorting to primal-dual splitting and the method of multipliers. Numerical experiments, implemented in parallel with CUDA, demonstrate the efficacy of the approach and its potential for high-dimensional data.

Fields of Study & Subjects

Medical Image Segmentation Techniques Distributed Control Multi-Agent Systems Neural Networks Stability and Synchronization

Publication details

Journal / source
Applied Mathematical Modelling
Publisher
Elsevier BV
Volume
158
Pages
116967–116967
Publication date
15 April 2026
Language
EN