公开(公告)号：US20230055391A1

公开(公告)日：2023-02-23

申请号：US17807215

申请日：2022-06-16

Applicant: Tata Consultancy Services Limited

Inventor： ARUSHI JAIN ,  SHUBHAM PALIWAL ,  MONIKA SHARMA ,  LOVEKESH VIG

IPC: G06F16/35 ,  G06F16/335 ,  G06F16/901 ,  G06K9/62

Abstract: State of art techniques that utilize spatial association based Table structure Recognition (TSR) have limitation in selecting minimal but most informative word pairs to generate digital table representation. Embodiments herein provide a method and system for TSR from an table image via deep spatial association of words using optimal number of word pairs, analyzed by a single classifier to determine word association. The optimal number of word pairs are identified by utilizing immediate left neighbors and immediate top neighbors approach followed redundant word pair elimination, thus enabling accurate capture of structural feature of even complex table images via minimal word pairs. The reduced number of word pairs in combination with the single classifier trained to determine the word associations into classes comprising as same cell, same row, same column and unrelated, provides TSR pipeline with reduced computational complexity, consuming less resources still generating more accurate digital representation of complex tables.