This paper aims to present a useful method for magnifying images, for which it is necessary to group the pixels and define the borders. In the proposed method, images are first partitioned using suitable segmentation algorithms and then artificial neural networks (ANNs) are applied to magnify each segment individually. In the ANNs applied, training is performed using, as input, a down-sampled form of the same image to be magnified. This type of training results in a high quality zoom in each segment since the pixels in an individual segment have very close features. Evaluation results on several images verifies the higher efficiency of the proposed method than other recently developed image zooming methods.