Ectopic beats are early heart beats remarkably different to the normal beat morphology that provoke serious disturbances in electrocardiographic analysis. These beats are very common in atrial fibrillation (AF), causing important residua when ventricular activity has to be removed for atrial activity (AA) analysis. In this work, a method is proposed to cancel out ectopics by discriminating between normal and abnormal beats, with an accuracy higher than 99%, through QRS morphological delineation and characterization. The most similar ectopics to the one under cancellation are clustered to provide a very precise cancellation template. Simulated and real AF recordings were used to validate the method. A new index, able to estimate the presence of ventricular residue after ectopics cancellation, was defined. Results by using the 2, 4, 6, …, 30 most similar ectopics to the one under study yielded optimal cancellation for templates composed of 10 beats. Furthermore, these beats were very likely located close to the ectopic under cancellation, which could facilitate the algorithm implementation. As conclusion, the proposed method is an effective way to remove ectopics from long term AF recordings and get them ready for the application of any QRST cancellation technique able to extract the AA in optimal conditions. Moreover, it could also detect, characterize and remove ectopics in any other type of non-AF recordings.