Research performed in the field of computer vision has steadily ignored recent advances in programming tools
and techniques, relying on well-established traditional methods, such as Unix-based C programming. While this
can certainly be effective, modern computer vision research may benefit significantly from the new tools and
technologies that have recently become available. This paper addresses the use of component-based
programming methods and proposes a model loosely based on 3-tier architectures, for the creation of robust and
reusable computer vision systems, in order to improve code modularity and reusability, and to ultimately foster
cooperation between researchers in the field. It outlines a basic design strategy and exposes the benefits and
drawbacks of migrating to component-based code. The model is used to build a component-driven framework
that is designed based on the principles of 3-tier applications. Its purpose is to aid in the creation and
maintenance of stable, dependable testing and development environments. We have listed the main advantages
of this approach and have concluded that although the learning curve for the programming skills required is
steep, the benefits to be reaped are worth it