Table to Text

The Aspose.OCR Table to Text for .NET Plugin specializes in recognizing and extracting tabular data from scanned images, PDFs, forms, or even photos of hand-drawn tables—exporting to CSV, Excel, JSON, or plain text.

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Table to Text Key Features

  1. Robust Table Structure Recognition Detects and extracts tables, rows, and columns with high accuracy—even from photos or imperfect scans.

  2. Flexible Export Formats Save recognized tables as CSV, XLSX, JSON, or plain text for seamless data reuse.

  3. Support for Complex and Nested Tables Handles multi-level headers, merged cells, and tables within forms or reports.

  4. Batch and Multi-Page Table Extraction Process multiple images or multi-page PDFs for large-scale digitization projects.

  5. Preprocessing for Clarity Enhance table detection with binarization, deskew, and denoising filters for challenging images.

  6. Watermark-Free Output Unlock full plugin functionality and watermark-free results by applying your metered license with SetMeteredKey().

Where Can the Table to Text Plugin Be Used?

  • Financial Reporting and Data Entry: Extract tabular data from bank statements, invoices, or balance sheets for import into Excel or BI tools.
  • Research and Academia: Digitize data tables from journals, lab books, or historical records for analysis.
  • Healthcare and Medical Records: Convert tables from patient charts, lab forms, or billing documents into searchable digital formats.
  • Government and Compliance: Process statistical tables or regulatory reports at scale.
  • Business and Operations: Automate data extraction from operational reports, audits, or receipts.

Basic Example: Extract Table Data from an Image 

using Aspose.OCR;

string tableFile = "table_scan.png";
OcrInput input = new OcrInput(InputType.SingleImage);
input.Add(tableFile);
RecognitionSettings settings = new RecognitionSettings();
settings.Language = Language.English;
settings.DetectAreasMode = DetectAreasMode.TABLE;
AsposeOcr ocr = new AsposeOcr();
var results = ocr.Recognize(input, settings);
Console.WriteLine(results[0].RecognitionText);
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