公开(公告)号：US12124797B2

公开(公告)日：2024-10-22

申请号：US17427279

申请日：2020-01-22

Applicant: Nippon Telegraph and Telephone Corporation

Inventor： Ikuko Takagi ,  Shiro Ogasawara ,  Koji Tsuji

IPC: G06K9/00 ,  G06F40/186 ,  G06F40/194 ,  G06V30/14 ,  G06V30/412 ,  G06V30/416

CPC classification number: G06F40/194 ,  G06F40/186 ,  G06V30/1448 ,  G06V30/412 ,  G06V30/416 ,  G06V2201/01

Abstract: An information processing device (10) acquires a plurality of ledger sheets having the same layout, compares the contents of each column at the same position each of the acquired plurality ledger sheets having the same layout, discriminates the type of each column according to the comparison result, and stores the information on the type of each column in a storage unit (14). Moreover, the information processing device (10) acquires position information of a processing target ledger sheet, compares information on the type of a column and the content of each column using information on a registered style with respect to the acquired ledger sheet, discriminates the type of each column of the processing target ledger sheet according to the comparison result, and specifies style candidates of the processing target ledger sheet on the basis of the discrimination result.

公开(公告)号：US11810374B2

公开(公告)日：2023-11-07

申请号：US17240097

申请日：2021-04-26

Applicant: Adobe Inc.

Inventor： Zhaowen Wang ,  Hailin Jin ,  Yang Liu

IPC: G06V20/62 ,  G06V30/148 ,  G06F18/214 ,  G06V10/764

CPC classification number: G06V20/62 ,  G06F18/214 ,  G06V10/764 ,  G06V20/63 ,  G06V30/153 ,  G06V2201/01

Abstract: In implementations of recognizing text in images, text recognition systems are trained using noisy images that have nuisance factors applied, and corresponding clean images (e.g., without nuisance factors). Clean images serve as supervision at both feature and pixel levels, so that text recognition systems are trained to be feature invariant (e.g., by requiring features extracted from a noisy image to match features extracted from a clean image), and feature complete (e.g., by requiring that features extracted from a noisy image be sufficient to generate a clean image). Accordingly, text recognition systems generalize to text not included in training images, and are robust to nuisance factors. Furthermore, since clean images are provided as supervision at feature and pixel levels, training requires fewer training images than text recognition systems that are not trained with a supervisory clean image, thus saving time and resources.