An Algorithm based on the polar Hough Transform has been developed so as to carry out rotation, translation and size-scaling invariant pattern recognition. The algorithm exploits the fundamental properties of the HT and all the required operations take place strictly in Hough space. The developed system has been successfully applied to the recognition of biscuits in the form of rectangular crackers, including f!awed pieces, which were easily discriminated against by the algorithm. The results suggest the possibility of an industrial application of this algorithm particularly in industrial quality control. © 2002 CSI. All rights reserved

A faster algorithm, the selective dynamics releasing frame (SORF), to computer-simulate the stochastic aggregation of diffusing particles is introduced. The SORF is presented making reference to the OLA model of Witen & Sander, however it can be applied to any OLA-Iike model which simulates cluster growth by diffusion. Traditional OLA-like models use the longest radius of the growing aggregate to control the radius of a Circular Launching Frame from where the particles are released to diffusion. The SORF uses the different radii of the regions of the growing cluster to fix a particular distance from where to release the particles to diffusion in every region. In bi-dimensional OLA simulations, a reduction in 30% of computer time was observed when the SORF was used. The algorithm here introduced is for a bi­ dimensional simulation, however its application to higher dimensions is stra...