Paper
21 December 2000 Scalable DSP architecture for high-speed color document compression
Michael Thierschmann, Kai-Uwe Barthel, Uwe-Erik Martin
Author Affiliations +
Proceedings Volume 4307, Document Recognition and Retrieval VIII; (2000) https://doi.org/10.1117/12.410833
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States
Abstract
The processing of colored documents with Document Management Systems (DMS) is possible with the modern document scanning systems today. Because of the enormous amount of image data generated scanning a typical A4 document with a 300 dpi resolution, image compression is used. The JPEG compression scheme is widely used for such image data. The lack of image quality caused by necessary lossy compression, can significantly reduce the recognition quality of a subsequent optical character recognition (OCR) process, which is essential to any DMS system. LuraDocument, a high performance system for compressing and archiving scanned documents, particularly those containing text and image, is overcoming the gap between high compression and legibility of documents suitable to be managed inside DMS systems. The utilization of LuraDocument results in substantially higher image quality in comparison to standard compression techniques. This high quality is achieved by combining automatic text detection with bitonal compression of text and color/grayscale wavelet compression of images. Since the innovative LuraDocument compression scheme is a complex image processing system, allocating some computational performance, a scalable DSP system has been designed to meet the throughput of high- performance document scanners.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael Thierschmann, Kai-Uwe Barthel, and Uwe-Erik Martin "Scalable DSP architecture for high-speed color document compression", Proc. SPIE 4307, Document Recognition and Retrieval VIII, (21 December 2000); https://doi.org/10.1117/12.410833
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CITATIONS
Cited by 6 scholarly publications and 1 patent.
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KEYWORDS
Image compression

Image segmentation

Quantization

Image processing

Wavelets

Image quality

Digital signal processing

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