This paper presents a new approach to off-line handwritten numeral recognition. From the concept of perturbation due to writing habits and styles, we propose a recognition method which is able to account for a variety of distortions. We tested our method on totally unconstrained numerals from the CEDAR database and obtained 99.1% correct recognition rate, which is the highest rate ever reached on this database.