Multi-mode PDF content purification and intelligent checking system and method based on visual perception enhancement

The multimodal PDF content purification system with enhanced visual perception utilizes deep convolutional networks and Transformer models for image-text association repair, solving the problems of limited parsing capabilities and poor cross-platform compatibility in existing PDF processing technologies, and achieving efficient document purification and intelligent review.

CN122113866APending Publication Date: 2026-05-29DATA TRANSMISSION GRP
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Patent Information

Application Number
CN202610229397.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-26
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing PDF processing technologies suffer from limitations in parsing capabilities, rigid noise tolerance mechanisms, lack of semantic association, and poor cross-platform compatibility during the circulation, editing, and archiving of digital documents. This leads to problems such as structural breaks, garbled characters, missing elements, disruption of text continuity, font replacement, and misaligned table lines during format restoration.

Method used

A multimodal PDF content cleanup system based on enhanced visual perception is adopted. The system generates multi-resolution image sequences through the visual perception module, identifies text regions using deep convolutional networks and OCR technology, performs semantic understanding by combining knowledge graphs and Transformer models, repairs the image-text association, and performs cross-platform verification and dynamic threshold adjustment through the intelligent decision module.

Benefits of technology

It achieves accurate identification and noise filtering of the fine structure of documents, automatically corrects formatting errors, improves the accuracy of text feature extraction and cross-platform display consistency, reduces the risk of excessive correction by manual review, supports multi-format output, and is suitable for deep cleaning and intelligent review of various electronic documents.

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Abstract

The invention belongs to the technical field of digital publication processing, and provides a multi-mode PDF content purification and intelligent review system and method based on visual perception enhancement, the system comprises a visual perception module, a semantic understanding module and an intelligent decision module, the visual perception module generates a multi-resolution image, extracts fine structure features and locates invisible characters, and the visual perception module carries out visual perception and semantic understanding. Eliminating physical layer interference; the semantic understanding module is used for constructing a knowledge graph and a DST-Transform model to realize character recognition, semantic coding and image-text association repair; the intelligent decision-making module achieves full-process processing from physical layer analysis to logic layer reconstruction to intelligent output through the steps of weighted calculation of confidence, dynamic threshold adjustment and cross-platform verification and output of the purified document, the PDF content purification accuracy and cross-platform compatibility are improved, and the method is suitable for deep purification and verification of the electronic document.
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