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Computational grids have become an imperative rising platform for high-performance computing. However, the grid and the grid applications development are still far from being affirmed, which is mainly due to the undeveloped grid-enabled computing environments. For that reason in this paper we propose a toolbox, called GrIPLab 1.0 (Grid Image Processing Laboratory), that aims at providing high performance image-processing platform in a grid computing environment by using the GLite middleware developed in the EGEE project. GrIPLab 1.0 is a combination of vision algorithms (the most common and some novel approaches) on which complex distributed vision applications can be modeled as a simple sequence of choices in a user friendly interface. Therefore, the main advantage of the presented dynamic grid toolbox is that provides a novel and comfortable access for scientific software developers and users without prior knowledge of grid technologies or even the underlying architecture. In this paper, we discuss the infrastructure that provides flexible and useful mechanism to achieve series image processing operations and we analyze the advantages of using such a system.