Gaussian descriptors are contourbased shape features. They are invariant to translation, scaling changes, rotation and reflection. Compared to the existing shape features, they are more robust against noise and slight edge variations, and have lower computation complexity and higher recognition/retrieval rate. In addition, they are applicationindependent. In this paper, Gaussian descriptors were used as features for character recognition. A comparison with another contourbased moment invariants, which is an improvement and extension of classical Hu moments, was also given. Numerical experimental results show that Gaussian descriptors are an attractive tool for character recognition.