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An algorithm for allocating and scheduling tasks in multiprocessor environments is presented. Its main characteristic is its orientation towards machine vision applications. In this sense it deals with the peculiarities of systems which combine generic-type processors with Image Acquisition and Processing Boards. The main goal of the algorithm is total processing time reduction; such are the requirements when we deal with automated industrial inspection applications. By simultaneously tackling the phases of allocation and scheduling, the results obtained are better than those offered by traditional algorithms. The system is applied to a process of citrus fruit inspection, and its performances are also evaluated over randomly generated task graphs.

A fully integrated development tool for computer vision systems has been built in the framework of this paper. There are many applications that help the user in the design of such systems, using graphical interfaces and function libraries. Even in some cases, the final source code can be generated by these applications. This paper goes a step beyond; it allows the development of computer vision systems from a distributed environment. Besides, and as a distinctive characteristic with regard to other similar utilities, the system is able to automatically optimize task scheduling and assignment, depending on the available hardware.