公开(公告)号：US20220351356A1

公开(公告)日：2022-11-03

申请号：US17243887

申请日：2021-04-29

Applicant: KYOCERA Document Solutions Inc.

Inventor： Kilho Shin ,  Kendrick Esperanza Wong

IPC: G06T7/00 ,  G06N3/08

Abstract: A system employs a trained model to detect artifact(s) associated with artifact type(s) appearing in a reproduction of a source image (a test image). The system determines differences between the test image and the source image and outputs probabilities that the artifact(s) in the test image are associated with each of the artifact type(s). A dataset for training the model includes: (i) a reference category including reference image(s) without any artifacts; and (ii) artifact categories, each corresponding to a respective one of the artifact types and including noised images associated with the respective artifact type. Each noised image includes one of the reference images and an artifact associated with the respective artifact type. The model is trained to detect the artifact type(s) by providing the model with the dataset and causing the model to process differences between each noised image and the reference image in the noised image.