公开(公告)号：US20230094787A1

公开(公告)日：2023-03-30

申请号：US17490610

申请日：2021-09-30

Applicant: Adobe Inc.

Inventor： Ankit Bal ,  Mohit Gupta ,  Ram Bhushan Agrawal ,  Tarun Verma ,  Uttam Dwivedi

IPC: G06K9/34 ,  G06T3/60 ,  G06N20/00

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately enhancing optical character recognition with a machine learning approach for determining words from reverse text, vertical text, and atypically-sized text. For example, the disclosed systems segment a digital image into text regions and non-text regions utilizing an object detection machine learning model. Within the text regions, the disclosed systems can determine reverse text glyphs, vertical text glyphs, and/or atypically-sized text glyphs utilizing an edge based adaptive binarization model. Additionally, the disclosed systems can utilize respective modification techniques to manipulate reverse text glyphs, vertical text glyphs, and/or atypically-sized glyphs for analysis by an optical character recognition model. The disclosed systems can further utilize an optical character recognition model to determine words from the modified versions of the reverse text glyphs, the vertical text glyphs, and/or the atypically-sized text glyphs.

公开(公告)号：US12288406B2

公开(公告)日：2025-04-29

申请号：US17490610

申请日：2021-09-30

Applicant: Adobe Inc.

Inventor： Ankit Bal ,  Mohit Gupta ,  Ram Bhushan Agrawal ,  Tarun Verma ,  Uttam Dwivedi

IPC: G06T9/00 ,  G06N3/0442 ,  G06N3/0455 ,  G06N3/0464 ,  G06N3/047 ,  G06N3/0475 ,  G06N3/084 ,  G06N5/01 ,  G06N7/01 ,  G06N20/00 ,  G06N20/10 ,  G06N20/20 ,  G06T3/60 ,  G06V30/148 ,  G06V30/162 ,  G06V30/262 ,  G06V30/413

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately enhancing optical character recognition with a machine learning approach for determining words from reverse text, vertical text, and atypically-sized text. For example, the disclosed systems segment a digital image into text regions and non-text regions utilizing an object detection machine learning model. Within the text regions, the disclosed systems can determine reverse text glyphs, vertical text glyphs, and/or atypically-sized text glyphs utilizing an edge based adaptive binarization model. Additionally, the disclosed systems can utilize respective modification techniques to manipulate reverse text glyphs, vertical text glyphs, and/or atypically-sized glyphs for analysis by an optical character recognition model. The disclosed systems can further utilize an optical character recognition model to determine words from the modified versions of the reverse text glyphs, the vertical text glyphs, and/or the atypically-sized text glyphs.