Shape feature extraction and classification

System and method for analyzing an image. A received image, comprising an object or objects, is optionally preprocessed. Invariant shape features of the object(s) are extracted using a generalized invariant feature descriptor. The generalized invariant feature descriptor may comprise a generalized invariant feature vector comprising components corresponding to attributes of each object, e.g., related to circularity, elongation, perimeter-ratio-based convexity, area-ratio-based convexity, hole-perimeter-ratio, hole-area-ratio, and/or functions of Hu Moment 1 and/or Hu Moment 2. Non-invariant features, e.g., scale and reflection, may be extracted to form corresponding feature vectors. The object is classified by computing differences between the generalized invariant feature vector (and optionally, non-invariant feature vectors) and respective generalized invariant feature vectors corresponding to reference objects, determining a minimum difference corresponding to a closest reference object or class of reference objects of the plurality of reference objects, and outputting an indication of the closest reference object or class as the classification.