PURPOSE: To prevent an unlearned image from being recognized erroneously as a specific image by recognizing it positively as the unlearned image, when the unlearned image is inputted.

CONSTITUTION: An output layer 13 of a neural network 1 to which a back propagation rule is adopted as a learning rule is provided with not only a cell Z1 learned by allowing it to correspond to a specific image being a multi- gradation image, and a cell Z2 learned by allowing it to correspond to an image similar to the specific image, but also a cell 23 for eliminating an unlearned image, learned by allowing it to correspond to an image of a plural gradation portion, whose whole surface is painted out by density of one gradation. This cell 23 catches other part than a feature of the specific image and the image being similar thereto as a feature of the image being distinctly different therefrom, when other unlearned image than the specific image and the image being similar thereto is inputted, its output value becomes larger than those of the cells Z1, Z2. In such a manner, the unlearned image is eliminated positively, and an erroneous recognition is prevented.