The Zernike Moments (ZM) have been successfully applied to the problem of shape recognition. Their properties allow for solving some fundamental problems in this task. Amongst them the most important one is the invariance to rotation, scaling, translation, and reflectional symmetry. Moreover, the obtained representation can vary according to the level of generalisation of a shape. For this reason in the paper the application of the ZM to the problem of General Shape Analysis (GSA) is proposed and experimentally investigated. The GSA problem is similar to the recognition and retrieval of shapes. However, only the most general classes of shapes (e.g. square, triangle, circle, ellipse) are assumed to perform the role of the basic templates. Moreover, the processed object does not have to belong to any of the template classes, but may be only similar to one of them. This enables us to receive the most general information about a shape, e.g. how square, triangular, round, elliptical, etc. it is. In the paper, in order to evaluate the Zernike Moments applied to the problem of GSA, the performance of this shape descriptor is compared with the results provided by nearly two hundred humans and collected by means of appropriate inquiry forms.