1. A computer-implemented method for analyzing an image, the method comprising one or more computers implementing: receiving an image, wherein the image is stored in a memory, and wherein the image comprises an object; extracting, by software executing on the computer, invariant shape features of the object using a generalized invariant feature descriptor, wherein the invariant shape features are features that are invariant with respect to scale, translation, rotation and symmetry, wherein the generalized invariant feature descriptor comprises a generalized invariant feature vector that represents attributes of the object in an invariant feature space defined by components of the generalized invariant feature descriptor, wherein the generalized invariant feature vector specifies a position in the invariant feature space, wherein the generalized invariant feature vector comprises comprising components corresponding to: roundness of the object; compactness of the object; holes of the object; and Hu Moments of the object; and classifying the object based on the extracted invariant shape features, wherein said classifying comprises comparing the position specified by the generalized invariant feature vector with positions of a plurality of corresponding generalized invariant feature vectors or partitions of the invariant feature space representing respective objects or classes of objects, and wherein said classifying comprises storing information classifying the object in a computer memory.