Artículo técnico

PDFlibPas: text, image, and font extraction in Delphi

losLab PDF Library ofrece a los equipos de Delphi y C++Builder un motor PDF con código fuente disponible para flujos de escritorio, servidor, DLL, ActiveX y Dylib, con comprobaciones PDF/A y PDF/UA integradas, soporte de firma PAdES y opciones de renderizado sin enviar documentos a un servicio PDF externo.

Este artículo está dirigido a teams building PDF analysis, migration, search, evidence capture, or support-inspection tools. Presenta text, image, and font extraction como una práctica de ingeniería documental para producción, no como una llamada aislada al componente.

El riesgo principal es que extraction output is easy to over-trust even though PDF content order, font encoding, image color spaces, and page resources rarely match user-visible reading order exactly. Por eso el flujo necesita contrato escrito, diagnósticos observables y archivos de regresión reales.

Decisiones de arquitectura

Separate extraction facts from interpretation. whether output needs visual order, content-stream order, or search-oriented order / image extraction format, color conversion, compression retention, and naming

  • whether output needs visual order, content-stream order, or search-oriented order
  • image extraction format, color conversion, compression retention, and naming
  • font subset naming, encoding diagnostics, and missing ToUnicode handling
  • confidence flags for OCR layers, hidden text, clipped content, and rotated pages

Flujo de implementación

Preserve page and resource context. The order below keeps the workflow reviewable for Delphi and C++Builder teams.

  1. scan page resources and content streams while preserving object references
  2. extract text runs with coordinates, font identity, Unicode mapping, and style signals
  3. extract images with page location, dimensions, color space, and original object data when needed
  4. classify fonts by subset, embedded status, and encoding behavior
  5. produce an analysis report that distinguishes facts from inferred reading order

Evidencia de validación

Extraction evidence that remains explainable. Keep these fields with the output or support record.

  • page number, object reference, coordinates, decoded text, font, and confidence
  • image size, color space, compression, mask, and export filename
  • font subset name, embedded state, encoding map, and ToUnicode status
  • warnings for hidden, clipped, rotated, or overlapping content

Extracted text is not always authored text

A professional extraction workflow should record where each text run, image, and font resource came from, how it was decoded, and which assumptions were used to group it into searchable or reviewable content.

Support package design

Once PDFlibPas is deployed, the most valuable support package is the one that explains the input, profile, output, and exact stage that failed.

  • page number, object reference, coordinates, decoded text, font, and confidence
  • image size, color space, compression, mask, and export filename
  • font subset name, embedded state, encoding map, and ToUnicode status
  • warnings for hidden, clipped, rotated, or overlapping content
  • terminology snapshot: text extraction, image extraction, font resource, ToUnicode

Engineering review notes for text, image, and font extraction

Use these review notes to make sure the feature has moved beyond a demo and can be defended during release, support, and customer escalation.

  • Decision: whether output needs visual order, content-stream order, or search-oriented order. Implementation pressure point: extract text runs with coordinates, font identity, Unicode mapping, and style signals. Acceptance evidence: font subset name, embedded state, encoding map, and ToUnicode status. Regression trigger: OCR layers can contain stale or misaligned text over scanned pages
  • Decision: image extraction format, color conversion, compression retention, and naming. Implementation pressure point: extract images with page location, dimensions, color space, and original object data when needed. Acceptance evidence: warnings for hidden, clipped, rotated, or overlapping content. Regression trigger: PDF drawing order may not equal human reading order
  • Decision: font subset naming, encoding diagnostics, and missing ToUnicode handling. Implementation pressure point: classify fonts by subset, embedded status, and encoding behavior. Acceptance evidence: page number, object reference, coordinates, decoded text, font, and confidence. Regression trigger: ligatures and custom encodings can make copied text differ from visible text
  • Decision: confidence flags for OCR layers, hidden text, clipped content, and rotated pages. Implementation pressure point: produce an analysis report that distinguishes facts from inferred reading order. Acceptance evidence: image size, color space, compression, mask, and export filename. Regression trigger: images may be masks, soft masks, or repeated resources rather than standalone pictures
  • Decision: whether output needs visual order, content-stream order, or search-oriented order. Implementation pressure point: scan page resources and content streams while preserving object references. Acceptance evidence: font subset name, embedded state, encoding map, and ToUnicode status. Regression trigger: OCR layers can contain stale or misaligned text over scanned pages
  • Decision: image extraction format, color conversion, compression retention, and naming. Implementation pressure point: extract text runs with coordinates, font identity, Unicode mapping, and style signals. Acceptance evidence: warnings for hidden, clipped, rotated, or overlapping content. Regression trigger: PDF drawing order may not equal human reading order
  • Decision: font subset naming, encoding diagnostics, and missing ToUnicode handling. Implementation pressure point: extract images with page location, dimensions, color space, and original object data when needed. Acceptance evidence: page number, object reference, coordinates, decoded text, font, and confidence. Regression trigger: ligatures and custom encodings can make copied text differ from visible text

Casos límite

  • PDF drawing order may not equal human reading order
  • ligatures and custom encodings can make copied text differ from visible text
  • images may be masks, soft masks, or repeated resources rather than standalone pictures
  • OCR layers can contain stale or misaligned text over scanned pages

Delphi / C++Builder notes

PDFlibPas should sit behind a small service boundary that receives files, streams, profiles, and credentials, then returns output paths, warnings, metrics, and validation status. Important terms include text extraction, image extraction, font resource, ToUnicode, content stream, coordinates.

Ejemplo de código Delphi

El siguiente esquema en Delphi muestra un límite de servicio práctico para este tema. Mantén las comprobaciones de política, el registro y la validación fuera del bloque estrecho que llama al producto para que el flujo sea comprobable.

procedure ExtractForIndexing(const FileName, OutputDir: string);
var
  Pdf: TPDFlib;
begin
  Pdf := TPDFlib.Create;
  try
    Pdf.LoadFromFile(FileName, '');
    SaveExtractedText(OutputDir, ExtractDocumentText(Pdf));
    SaveEmbeddedImages(OutputDir, ExtractDocumentImages(Pdf));
    SaveFontInventory(OutputDir, BuildFontInventory(Pdf));
  finally
    Pdf.Free;
  end;
end;

Lista de salida a producción

  • Run the workflow on an empty file, a normal customer file, and a worst-case file
  • Open the generated PDF with the target viewer, validator, printer, or downstream application
  • Log product version, profile version, input hash, output path, elapsed time, and warning count
  • Keep passwords, certificates, temporary files, and customer data under explicit retention rules
  • Add regression documents when a customer file exposes a new edge case

Product documentation

PDFlibPas