In computer vision several methods are directly inspired by the human visual system. Visual attention is one of the main abilities a human eye uses to discover a new scene. This ability is based on the focus of attention principle, which enables to look at a particular point. The works presented in this paper describe how to simulate such an ability in computer vision. Color images are resampled according to this principle, in order to considerably decrease the amount of data to be processed. This resampling is done by using a concentric distribution of hexagonal cells instead of the rectangular cell grid generally provided by uniform sensors such as CCD cameras. Such a distribution is derived from the cone distribution on the retina and the result is encoded by using polar coordinates. In this way the information is more and more blurred in an isotropic way, when getting far and far from the focusing point. This resampling method then allows decreasing data number while it globally keeps all the information included in the image. In this way a new scene can be explored by focusing successively at a sequence of focusing points. This allows reproducing the human eye behavior that explores a new scene by saccades. Furthermore the resampled images can be used in order to set up image preprocessing. For example this resampling can be achieved before a preliminary step of segmentation. The resampled image is segmented in order to coarsely determine regions. Afterwards the segmentation step can be refined by combining the segmented resampled image and the original image. A comparison between results obtained in RGB and HSV spaces is also given on a set of images.