Processing speed is important when high volumes of scanned pages of paper documents have to be processed/converted using Optical Character Recognition. Below some on this topic,

• Optical Character Recognition is
  • a multi-step process and each of the processing step can be very CPU intense (e.g. image pre-processing or layout analysis)
  • a high number of images and PDFs require fast hard disk throughput
  • processing speed also depends on the the material, for example the document type, image quality, languages

• OCR quality and processing speed are linked, the general rule is
  • Recognition quality is direct proportional to the required processing time
  • Low quality documents need more CPU time and are processed slower than document images in high quality

There is some general “wisdom”

• the better the image quality, the faster the images can be processed
  • From version 10 on FineReader Engine offers a new fast mode that is especially tuned for good quality images
  • If the image quality is not known before, it is recommend to use the “balanced mode”, here the technology makes the “internal” decision.
• when the image quality is bad, a lot more (CPU) time has to be “invested” to get the best possible results
  • cleaning images
  • rotating images
  • FineReader Engine Windows contains a (pre-compiled) code sample that makes it easy to the influence of image preprocessing on the over all processing speed

• Complex layouts need more time for document analysis that simple book pages
• Reading “low quality” characters takes more time than processing “clean” characters.

• The total processing time is a sum of the different internal processing steps
  • different technologies will take different times
    • this is true for different ABBYY technology cycles
    • and of course also when different technologies from different vendors are compared.
  • never the less, to get good recognition results on low quality images a lot more efforts have to be made to get good/usable results
  • if a technology is only tuned for speed, then it will not be able to deliver acceptable results on low quality documents

• The processing time / throughput of one CPU core is not the final achievable speed of a production installation, because the number of CPU cores is growing with every new CPU generation.
  • To scale up throughput an effective use of multiple cores has to be considered
  • To be able to use multiple CPU cores on one or multiple machines the licensing scheme has to allow this

• The type of OCR processing also influences the processing time/throughput
  • Pure text extraction without document layout retention is faster than exporting to a format where the layout has to be reconstructed. Further details on
    • OCR & Document Conversion Processing Profiles
    • there is also a precompiled code sample for simplified testing
  • Image-resolution changes and MRC compression of the generated PDFs will influence the processing speed
    • PDF Export Profile Sample can be used for custom tests

The good news - OCR Scalability is available built in in ABBYY SDKs and there are several approaches to speed up processing

• The latest versions of FineReader Engine and FlexiCapture Engine support Multi Core CPUs
  Details can be found on the code sample articles:
  • Multi-Core OCR Processing Sample
  • Batch OCR Processing Sample FineReader Engine 10/11
  • FineReader Engines Pool - Multithreading Sample - New V11
  • Multi-Core Processing in FlexiCapture Engine

• The ABBYY Licensing scheme offers “scalability” - so it is possible to scale up processing.
  • A one machine license with allows unlimited CPU cores, when a page limit (renewable or total), a Character limit (renewable or total) or a speed limit are set
  • A network license allows to scale up the processing to a very high number of machines (virtual or physical) and also all CPU cores can be used.

• OCR Recognition Modes - Quality or speed or balanced recognition mode
• Image Processing and Binarisation for Camera OCR - image pre-processing and recognition speed

• OCR SDK Scalability - boosted processing with multiple CPU cores
• Network Licensing - use multiple machines to scale up

• Code Sample articles on Multi-Core Support and Processing Profiles:
  • Code Samples Collection
  • Predefined OCR Processing Profiles Sample (FRE) - Quality/Speed Profiles for different processing scenarios

• OCR Accuracy Measurement
• Cloud OCR Scalability

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