&lt;title&gt;Recognition system rapid application prototyping tool&lt;/title&gt;

Mills, Stuart; Karins, James P.; Dydyk, Robert Barry

doi:10.1117/12.270366

Cited by 4 publications

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“…The functionality of the OC was simulated using specialized software: Optical Recognition Simulation Software [4]. This software was developed by Litton Data Systems to enable rapid prototyping and testing of optical recognition systems.…”

Section: Sample Resultsmentioning

confidence: 99%

<title>Automated search and retrieval of information from imaged documents using optical correlation techniques</title>

Stalcup¹,

Dennis²,

Dydyk³

1999

SPIE Proceedings

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Today, the paper document is fast becoming a thing of the past. With the rapid development of fast, inexpensive computing and storage devices, many government and private organizations are archiving their documents in electronic form (e.g., personnel records, medical records, patents, etc.). Many of these organizations are converting their paper archives to electronic images, which are then stored in a computer database. Because of this, there is a need to efficiently organize this data into comprehensive and accessible information resources and provide for rapid access to the information contained within these imaged documents.To meet this need, Litton PRC and Litton Data Systems Division are developing a system, the Imaged Document Optical Correlation and Conversion System (IDOCCS), to provide a total solution to the problem of managing and retrieving textual and graphic information from imaged document archives. At the heart of IDOCCS, optical correlation technology provides the search and retrieval of information from imaged documents. IDOCCS can be used to rapidly search for key words or phrases within the imaged document archives. In addition, IDOCCS can automatically compare an input document with the archived database to determine if it is a duplicate, thereby reducing the overall resources required to maintain and access the document database. Embedded graphics on imaged pages can also be exploited; e.g. , imaged documents containing an agency's seal or logo can be singled out. In this paper, we present a description of IDOCCS as well as preliminary performance results and theoretical projections.

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Section: Sample Resultsmentioning

confidence: 99%

<title>Automated search and retrieval of information from imaged documents using optical correlation techniques</title>

Stalcup¹,

Dennis²,

Dydyk³

1999

SPIE Proceedings

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“…An interesting optical correlator software package has been developed by Litton [32]. It considers an optical correlator and 9 optical processing modules (processing functions) in scene analysis (these include: detection, segmentation, preprocessing, filter selection, correlator, post processor, identifier).…”

Section: Oe Manufacturing and Cadmentioning

confidence: 99%

Optical metrology for industrialization of optical information processing

Casasent¹,

Wilson²

1997

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One of the major barriers to commercial application of optical technology to information processing is the high cost of system development and manufacture. This problem has been solved in other industries through the use of computer aided design (CAD) and integration of system design with manufacturing. The development of better system level metrology is needed to allow more computer-based methods to be used in this process. As a test case, we are designing an optical pattern recognition system to be performed on an input image (at video rates) versus a large reference set, for example 1000 faces, with images of 640 by 480 pixels or larger. We have constructed both an optical pattern recognition system and a holographic memory system which we have instrumented and used to address the metrological needs of these applications. This has allowed us to evaluate the level of system and component level metrology needed for real-time video processing. This report addressed the metrological issues encountered in building and testing these systems.

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Pattern recognition prototyping tool

Mills¹,

Karins²,

Dydyk³

Proceedings of International Conference on Image Processing

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The Rapid Application Prototyping Tool for Object Recognition (RAPTOR) has been developed to assist system developers in the evaluation of template matching pattern recognition systems prior to hardware development. The tool consists of two parts: a hardware simulation and additional functionality to assist in the development process. The hardware simulation, based on the Litton Electro-optical Processor, consists of nine servers that can be used for various levels of system simulation. The support functionality consists of data base management and pattem recognition template generation tools. RAPTOR is designed for Intel (or compatible) based computers running Microsoft's Windows 95 or Windows NT 4.0 operating system. The system exploits Microsoft's Distributed Component Object Model (COM) technology. Sample results from three RAPTOR simulation applications are presented.

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<title>Recognition system rapid application prototyping tool</title>

Cited by 4 publications

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<title>Automated search and retrieval of information from imaged documents using optical correlation techniques</title>

<title>Automated search and retrieval of information from imaged documents using optical correlation techniques</title>

Optical metrology for industrialization of optical information processing

Pattern recognition prototyping tool

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