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iDocChip: A Configurable Hardware Accelerator for an End-to-End Historical Document Image Processing.

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A new portable system, iDocChip, enables accurate optical character recognition (OCR) for historical documents on the go. This low-power device significantly improves upon existing OCR software in speed and energy efficiency.

Keywords:
FPGAOCRZynqhardware architecturehardware-software co-designhistorical documentsimage processing

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Area of Science:

  • Digital humanities
  • Computer engineering
  • Information science

Background:

  • Increasing demand for digitized historical records necessitates efficient OCR solutions.
  • Existing OCR software (anyOCR) offers high accuracy but is not suitable for portable devices due to high computational complexity.
  • Portable scanning and OCR devices are required for digitizing records in situ.

Purpose of the Study:

  • To design and implement a portable, low-power, and energy-efficient system for accurate OCR of historical documents.
  • To develop a configurable hardware-software System-on-Chip (SoC) named iDocChip.
  • To optimize the anyOCR algorithm for real-time performance on portable devices.

Main Methods:

  • Designed and implemented a hybrid CPU-FPGA architecture for the iDocChip.
  • Developed optimized software implementations of the anyOCR algorithm for the iDocChip.
  • Evaluated the system's runtime, power consumption, and recognition accuracy on multiple platforms.

Main Results:

  • The iDocChip system demonstrated a 44x improvement in runtime compared to existing anyOCR.
  • Achieved 2201x higher energy efficiency with the iDocChip.
  • Obtained a 3.8% increase in recognition accuracy.

Conclusions:

  • The iDocChip provides a portable, real-time, and energy-efficient solution for digitizing historical records using OCR.
  • The hybrid CPU-FPGA architecture and optimized software enable high accuracy and performance on portable devices.
  • iDocChip significantly advances the accessibility and processing of historical archives.