It is used in many application areas to digitize document images like passports, invoices, and others. Optical character recognition (OCR) is the most common method of transcribing typed, handwritten, or printed documents into digital format. In the modern age, information is often provided and circulated as digital data. The iDocChip system outperforms the existing anyOCR by 44 × while achieving 2201 × higher energy efficiency and a 3.8 % increase in recognition accuracy. We demonstrate our results on multiple platforms with respect to runtime and power consumption. In this paper, we present the hybrid CPU-FPGA architecture of iDocChip along with the optimized software implementations of the anyOCR. As a low-power and energy-efficient system with real-time capabilities, the iDocChip delivers the required portability. Therefore, we have designed and implemented a configurable hardware-software programmable SoC called iDocChip that makes use of anyOCR techniques to achieve high accuracy. However, it is unsuitable for portable devices, as it exhibits high computational complexity resulting in long runtime and high power consumption. An existing end-to-end OCR software called anyOCR achieves high recognition accuracy for historical documents. However, to digitize these records without removing them from where they are archived, portable devices that combine scanning and OCR capabilities are required. Many libraries offer special stationary equipment for scanning historical documents. Optical character recognition (OCR) is typically applied to scanned historical archives to transcribe them from document images into machine-readable texts. In recent years, there has been an increasing demand to digitize and electronically access historical records.
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