Pierrick Legrand

Signal and Image processing with FracLab

We describe a software toolbox, called FracLab, for signal and image processing based on fractal and multifractal methods. We illustrate the use of FracLab on a numerical example, and give some new results for estimating fractal parameters in the course of the presentation.

Local regularity-based image denoising

We present an approach for image denoising based on the analysis of the local Holder regularity. The method takes the point of view that denoising may be performed by increasing the Holder regularity at each point. Under the assumption that the noise is additive and white, our procedure is asymptotically minimax, provided the original signal belongs to a ball in some Besov space. Such a scheme is well adapted to the case where the image to be recovered is itself very irregular, e.g. nowhere differentiable with rapidly varying local regularity. The method is implemented through a wavelet analysis. We show an application to SAR image denoising where this technique yields good results compared to other algorithms.

Artificial Evolution, 11th Internatioanl Conference, Evolution Artificielle, EA, 2013, Bordeaux, France, revised selected papers.

This LNCS volume includes the best papers presented at the 11th Biennial International Conference on Artificial Evolution, EA 2 2013, held in Bordeaux (France). Authors had been invited to present original work relevant to Artificial Evolution, including, but not limited to: Evolutionary Computation, Evolutionary Optimization, Co-evolution, Artificial Life, Population Dynamics, Theory, Algorithmics and Modeling, Implementations, Application of Evolutionary Paradigms to the Real World(industry, biosciences,...), other Biologically Inspired Paradigms (Swarm, Artificial Ants, Artificial Immune Systems, Cultural Algorithms...), Memetic Algorithms, Multi-Objective Optimization, Constraint Handling, Parallel Algorithms, Dynamic Optimization, Machine Learning, and hybridization with other soft computing techniques

Fractal properties and characterization of road profiles

A major problem in road engineering is to understand the mechanisms of friction between rubber and the road. We study road profiles obtained using tactile and laser captors. these profiles belong to different category characterized by different friction coefficients. We find that all our profiles indeed display strong fractal behaviour in terms of both correlation exponents and regularization dimension over a large range of scales. However, neither of these fractal parameters seem to be related to friction. We then use a local fractal parameter, namely the pointwise Holder exponent. We show that this exponent does discriminate profiles which have different friction properties.

Artificial Evolution 2015

This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Conference on Artificial Evolution, EA 2015, held in Lyon, France, in October 2015. The 18 revised papers were carefully reviewed and selected from 31 submissions. The focus of the conference is on following topics: Evolutionary Computation, Evolutionary Optimization, Co-evolution, Artificial Life, Population Dynamics, Theory, Algorithmics and Modeling, Implementations, Application of Evolutionary Paradigms to the Real World, Dynamic Optimization, Machine Learning and hybridization with other soft computing techniques.