This paper addresses the problem of automatic target recognition (ATR) using inverse synthetic aperture radar (ISAR) images. In this context, we propose a novel approach for feature extraction to describe precisely an aircraft target from ISAR images. In our approach, a visual attention model is adopted to separate the salient regions from the background. After that, the scale invariant feature transform (SIFT) method is used to extract the keypoints and their descriptors. Then, a local salient feature is built by considering only the keypoints located in the salient region. For the classification step, the support vector machines (SVM) classifier is adopted. To validate the proposed approach, ISAR images database which was collected from anechoic chamber is used.