A massively parallel approach to cellular neural networks image processing

Abstract

Low-level image processing is a critical phase, since the results of following "more intelligent" steps depend on the output quality of the first processing stages. In this work we present an edge detection filtering algorithm, strictly oriented to enhance the edge of some objects, in a typical real image noisy context, using some "a priori" known characteristics. We describe also an application of this algorithm to the analysis of road images, where the goal is the enhancement of traffic signs.<>