The fusion of regions from segmentation is often a required step in order to analyze objects in the scene. It allows to group under a same closure property the partitions of an image, which denote the same object. In this way, several studies have been made. Most of the algorithms are based on global information to evaluate the relevance of region combinations and fusion. In this paper, we propose a merging process based on Gestalt vision's theory. The particularity of our method is to preserve photographer's region of interest thanks to the definition of a new criterion based on Di Zenzo gradient. Thus, region fusion preserves photographer's relevant objects of the scene. The performance of the proposed method is evaluated using various natural images, including Berkeley image database and its accuracy is shown.