  Handwritten automatic character recognition has attracted many researchers
all over the world to contribute automatic character recognition domain. Shape
identification and feature extraction is very important part of any character
recognition system and success of method is highly dependent on selection of
features. However feature extraction is the most important step in defining the
shape of the character as precisely and as uniquely as possible. This is indeed
the most important step and complex task as well and achieved success by using
invariance property, irrespective of position and orientation. Zernike moments
describes shape, identify rotation invariant due to its Orthogonality property.
MODI is an ancient script of India had cursive and complex representation of
characters. The work described in this paper presents efficiency of Zernike
moments over Hus moment for automatic recognition of handwritten MODI numerals.
