Improved texture image classification through the use of a corrosion-inspired cellular automaton

In this paper, the problem of classifying synthetic and natural texture images is addressed. To tackle this problem, an innovative method is proposed that combines concepts from corrosion modeling and cellular automata to generate a texture descriptor. The core processes of metal (pitting) corrosion are identified and applied to texture images by incorporating the basic mechanisms of corrosion in the transition function of the cellular automaton. The surface morphology of the image is analyzed before and during the application of the transition function of the cellular automaton. In each iteration the cumulative mass of corroded product is obtained to construct each of the attributes of the texture descriptor. In a final step, this texture descriptor is used for image classification by applying Linear Discriminant Analysis. The method was tested on the well-known Brodatz and Vistex databases. In addition, in order to verify the robustness of the method, its invariance to noise and rotation were tested. To that end, different variants of the original two databases were obtained through addition of noise to and rotation of the images. The results showed that the method is effective for texture classification according to the high success rates obtained in all cases. This indicates the potential of employing methods inspired on natural phenomena in other fields.Comment: 13 pages, 14 figure

Formability optimisation of fabric preforms by controlling material draw-in through in-plane constraints

A genetic algorithm is coupled with a finite element model to optimise the arrangement of constraints for a composite press-forming study. A series of springs are used to locally apply in-plane tension through clamps to the fibre preform to control material draw-in. The optimisation procedure seeks to minimise local in-plane shear angles by determining the optimum location and size of constraining clamps, and the stiffness of connected springs. Results are presented for a double-dome geometry, which are validated against data from the literature. Controlling material draw-in using in-plane constraints around the blank perimeter is an effective way of homogenising the global shear angle distribution and minimising the maximum value. The peak shear angle in the double-dome example was successfully reduced from 48.2 degrees to 37.2 degrees following a two-stage optimisation process

Revisiting Some Developments of Boundary Elements for Thick Plates in Brazil

This work reviews the developments of Boundary Element Method formulations to solve several types of plate bending problems, including non-linear bending. The formulation is developed and solved using the standard BEM procedure, and different integration approaches were discussed and tested. Object oriented implementation issues are commented. Results were obtained for linear and non-linear elastic bending as well as buckling of selected cases of thick plates, including cases of step variation in thickness under large displacements regime

Lyapunov exponents of one-dimensional, binary stochastic cellular automata

In this paper the stability of elementary cellular automata (ECAs) upon introduction of stochasticity, in the form of an update probability for each cell, is assessed. To do this, Lyapunov exponents, which quantify the rate of divergence between two nearby trajectories in phase space, were used. Furthermore, the number of negative Lyapunov exponents was tracked, in order to gain a more profound insight into the interference between the stability and the update probability, and an upper bound on the Lyapunov exponents of stochastic cellular automata (SCAs) was established