Obtaining genericity for image processing and pattern recognition algorithms

Algorithm libraries dedicated to image processing and pattern recognition are not reusable; to run an algorithm on particular data, one usually has either to rewrite the algorithm or to manually “copy, paste, and modify”. This is due to the lack of genericity of the programming paradigm used to implement the libraries. In this paper, we present a recent paradigm that allows algorithms to be written once and for all and to accept input of various types. Moreover, this total reusability can be obtained with a very comprehensive writing and without significant cost at execution, compared to a dedicated algorithm. This new paradigm is called generic programming and is fully supported by the C++ language. We show how this paradigm can be applied to image processing and pattern recognition routines. The perspective of our work is the creation of a generic library