Research at protein level is a useful practice in personalized medicine. More specifically, 2D gel images obtained after electrophoresis process can lead to an accurate diagnosis. Several computational approaches try to help the clinicians to establish the correspondence between pairs of proteins of multiple 2D gel images. Most of them perform the alignment of a patient image referred to a reference image. In this work, an approach based on block-matching techniques is developed. Its main characteristic is that it does not need to perform the whole alignment between two images considering each protein separately. A comparison with other published methods is presented. It can be concluded that this method works over broad range of proteomic images, although they have a high level of difficulty.