Abstract: Provided is an information processing apparatus capable of preventing erroneous detection of an abnormality even in a case where a region other than an inspection target region appears in an image of an object or even in a case where the appearance of the object may partially vary because of the nature of the object. An information processing apparatus includes: a generating section that acquires an image and generates a reconstructed image based on the image; an identification section that identifies an inspection target region in the image based on the image; and a calculation section that calculates a difference in the inspection target region between the image and the reconstructed image.

Abstract: Provided are an index selection device, an information processing device, an information processing system, an inspection device, an inspection system, an index selection method, and an index selection program with improved accuracy of defect detection. The index selection device includes a score calculator 230 and an index selector 240. The score calculator 230 calculates abnormality scores of a non-defective product and a defective product by using a plurality of indices based on a plurality of pieces of input data of the non-defective product and the defective product and a plurality of pieces of reference data corresponding to the input data. The index selector 240 selects any one of the plurality of indices according to the abnormality scores of the non-defective product and the defective product.

Abstract: Stable determination accuracy is secured regardless of an image size, in abnormality detection of detecting a visual defect of an object. An abnormality detection system includes an input unit, a feature extractor, an image generator, and a detector. The input unit acquires inspection images of a target object, the inspection images having different image sizes each of which is equal to or more than a predetermined size. The feature extractor is previously learned to extract a feature map from training images including a non-defective image of the target object. The image generator is previously learned to restore the training images from the feature map extracted by the feature extractor. The detector compares the inspection image of the target object, which is an inspection target, the inspection image being input to the input unit, with a corresponding restored image restored from the inspection image by the feature extractor and the image generator.