In this paper, a concise method is proposed to locate the nipple position on a mammogram image. Mammogram registration is an important preprocessing technique, which can help in finding asymmetrical regions in left or the corresponding right breast. In particular, correct nipple position is the crucial key point of mammogram registration since it is still the most consistent and stable landmark on a mammogram. This work first presents an algorithm of maximum height of the breast border (MHBB) and then proposes two novel approaches, local spatial-maximum mean intensity (MMI) and local maximum zero-crossing (MZC) based on the second-order derivative, finally a combined process depending on the MMI and MZC is obtained. The 213 mammogram images from MIAS and 200 ones from DDSM database are tested for estimating the proposed method. Consequently, the mean Euclidean distance (MED) between the nipple position detected and the ground truth identified by the radiologist is 0.63 cm, within 1 cm of the gold standard. The experimental results hence indicate that our combined process can detect the nipple positions more accurately, as compared to other previous methods. Moreover, the proposed LVNM (Locate visible-nipple mammograms) algorithm designed with the generalization ability for automatic nipple clustering in the MIAS database has also yielded an identification rate of 99.53%.