Abstract: The present invention provides an apparatus and a method for classifying and recognizing image patterns using a second-order neural network, thereby achieving high-rate parallel processing while lowering the complexity. The second-order neural network, which is made of adders and multipliers, corrects positional translations generated in a complex-log mapping unit to output the same result for the same object irrespective of the scale and/or rotation of the object. The present invention enables high-rate image pattern classification and recognition based on parallel processing, which is the advantage obtained in neural network models, because consistent neural networks and consistent network structure computation models are applied to all steps from the image input step to the pattern classifying and recognizing step.