Registration of mammograms is an essential step to increase the effectiveness of all screening programs planned to early detect breast cancer in asymptomatic women. New techniques based on data fusion of different spatial views, temporal analysis or sequences follow up, and multimodal data analysis, require accurate data registration: forcing spatial alignment of images taken from different views, at different times or from different natures. In this work we will focus on a new technique for automatic bilateral mammograms registration. However the same registration technique is also useful for temporal analysis of the same patient. Bilateral mammogram registration is a challenging task; the mammographic appearance of breast tissue may vary considerably, because of differences in breast compression and positioning, differences in imaging techniques, and changes in the breast itself; moreover, there are no clear landmarks in a mammogram, except for the nipple when it is visible. In our approach we detect the skin-line contour as a first step, we describe the contour as a chain-code, and we make a wavelet based correlation analysis, finally we get the matching of the contours. At the end we apply a global affine transformation.