Automatic image registration remains a real challenge in several fields. Although several methods have been proposed for automatic image registration in recent years, it is still far from widespread use in several applications, such as remote sensing. In this document, a method is proposed for the automatic registration of images through the segmentation of images based on histograms (HAIRIS). This new approach consists mainly in combining several segmentations of the pair of images to be recorded, according to a relaxation parameter in the histogram modes delimitation (which in turn is a new approach), followed by a consistent characterization of the extracted objects , through the area objects, relationship between the axis of the fit ellipse, the perimeter and the fractal dimension, and a robust procedure based on statistics for object matching. The application of the proposed methodology is illustrated for simulated rotation and translation. The first set of data consists of a photograph and a rotated and shifted version of the same photograph, with different levels of added noise. It was also applied to a pair of satellite images with different spectral content and simulated translation, and to real examples of remote sensors comprising different viewing angles, different acquisition dates and different sensors. An accuracy of less than 1 ° was obtained for the rotation and at the level of subpxels for translation, in most of the situations considered. HAIRIS allows the registration of pairs of images (multitemporal and multisensor) with differences in rotation and translation, with small differences in spectral content, leading to subpixel accuracy.