The recent technological advance has attracted the industry and the academic community to research and propose methods, seek for new techniques, and formal languages for engineering design in order to respond to the growing demand for sophisticated product and systems that fully satisfy customers needs. It can be associated, for instance, with an application of object recognition using texture features, essential to a variety of applications domains, such as robotic vision, industrial inspection, remote sensing, security and medical image diagnosis. Considering the importance of the large number of applications mentioned before, and due to their characteristic where both application and developer domain are very close to each other, this work aims to present a design process based on ideas extracted from axiomatic design to accelerate the development for the classical approach to texture analysis. Thus, a case study is accomplished where a new conception of neural network architecture is specially designed for the following proposal: preserving the two-dimensional spatial structure of the input image, and performing texture feature extraction and classification within the same architecture. As a result, a new mechanism for neuronal competition is also developed as specific knowledge for the domain. In fact, the process proposed has some originality because it does take into account that the developer assumes also the customer's role on the project, and establishes the systematization process and structure of logical reasoning of the developer in order to develop and implement the solution in neural network domain. Lista de Tabelas 2.1 Características dos domínios envolvidos no Projeto Axiomático naś areas de manufatura, materiais, software, organização, sistema, negócios. 2.2 Relação {FR}-{DP} de acordo com a matriz de projeto. Adaptado