losLab PDF Library предоставляет командам Delphi и C++Builder PDF-движок с доступным исходным кодом для настольных, серверных, DLL, ActiveX и Dylib процессов, включая встроенные проверки PDF/A и PDF/UA, подписи PAdES и выбор рендерера без отправки документов во внешний PDF-сервис.
Эта статья предназначена для teams building PDF analysis, migration, search, evidence capture, or support-inspection tools. Она рассматривает text, image, and font extraction как промышленную инженерию документов, а не как одиночный вызов компонента.
Практический риск состоит в том, что 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. Поэтому процессу нужны письменный контракт, наблюдаемая диагностика и реалистичные регрессионные файлы.
Архитектурные решения
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
Порядок реализации
Preserve page and resource context. The order below keeps the workflow reviewable for Delphi and C++Builder teams.
- scan page resources and content streams while preserving object references
- extract text runs with coordinates, font identity, Unicode mapping, and style signals
- extract images with page location, dimensions, color space, and original object data when needed
- classify fonts by subset, embedded status, and encoding behavior
- produce an analysis report that distinguishes facts from inferred reading order
Доказательства проверки
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
Пограничные случаи
- 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.
Пример кода Delphi
Следующий эскиз Delphi показывает практическую границу сервиса для этой темы. Оставляйте проверки политики, журналирование и валидацию вне узкого блока вызова продукта, чтобы сценарий было проще тестировать.
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;Производственный чек-лист
- 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