7. The computer implemented method of classifying handwritten words according to claim 1 , wherein a Tangent Vector is computed for each individual character of a reference word, where 
 Tangent_Vector i =Transformation i (Image_ ref,α i )−Image_ ref, where i signifies that a computation or variable is specific to an individual character of the reference word, Image_ref is a reference image, and the function Transformation i ( ) is any transformation of the Image_ref by a parameter α i .
7. The computer implemented method of classifying handwritten words according to claim 1 , wherein a Tangent Vector is computed for each individual character of a reference word, where 
 Tangent_Vector i =Transformation i (Image_ ref,α i )−Image_ ref, where i signifies that a computation or variable is specific to an individual character of the reference word, Image_ref is a reference image, and the function Transformation i ( ) is any transformation of the Image_ref by a parameter α i . 8. The computer implemented method of classifying handwritten words according to claim 7 , wherein a linear approximation to a transformation is computed, the linear approximation being given by the equation: 
 Image_ ref+p *Tangent_Vector, where p is a parameter adjustable from −1 to +1, and Tangent_Vector comprises one or more Tangent_Vector i tangent vectors.