1. Automatic identification and data capture
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Automatic identification and data capture (AIDC) refers to the methods of automatically
identifying objects, collecting data about them, and entering that data directly into computer
systems (i.e. without human involvement). Technologies typically considered as part of AIDC
include bar codes, Radio Frequency Identification (RFID), biometrics, magnetic stripes, Optical
Character Recognition (OCR), smart cards, and voice recognition. AIDC is also commonly
referred to as “Automatic Identification,” “Auto-ID,” and "Automatic Data Capture."
AIDC is the process or means of obtaining external data, particularly through analysis of images,
sounds or videos. To capture data, a transducer is employed which converts the actual image or a
sound into a digital file. The file is then stored and at a later time it can be analyzed by a
computer, or compared with other files in a database to verify identity or to provide authorization
to enter a secured system. Capturing of data can be done in various ways; the best method
depends on application.
AIDC also refers to the methods of recognizing objects, getting information about them and
entering that data or feeding it directly into computer systems without any human involvement.
Automatic identification and data capture technologies include barcodes, RFID, bokodes, OCR,
magnetic stripes, smart cards and biometrics (like iris and facial recognition system).
In biometric security systems, capture is the acquisition of or the process of acquiring and
identifying characteristics such as finger image, palm image, facial image, iris print or voice
print which involves audio data and the rest all involves video data.
Radio frequency identification (RFID) is relatively a new AIDC technology which was first
developed in 1980’s. The technology acts as a base in automated data collection, identification
and analysis systems worldwide. RFID has found its importance in a wide range of markets
including livestock identification and Automated Vehicle Identification (AVI) systems because
of its capability to track moving objects. These automated wireless AIDC systems are effective
in manufacturing environments where barcode labels could not survive.
Contents
1 Capturing data from printed documents
2 The Internet and the future
3 AIDC 100
4 See also

2. 5 References
Capturing data from printed documents
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One of the most useful application tasks of data capture is collecting information from paper
documents and saving it into databases (CMS, ECM and other systems). There are several types
of basic technologies used for data capture according to the data type:[citation needed]
OCR – for printed text recognition[citation needed]
ICR – for hand-printed text recognition[citation needed]
OMR – for marks recognition[citation needed]
OBR – for barcodes recognition[citation needed]
BCR – for business cards recognition[citation needed]
DLR - for document layer recognition[citation needed]
These basic technologies allow extracting information from paper documents for further
processing it in the enterprise information systems such as ERP, CRM and others.[citation needed]
The documents for data capture can be divided into 3 groups: structured, semi-structured and
unstructured.[citation needed]
Structured documents (questionnaires, tests, insurance forms, tax returns, ballots, etc.) have
completely the same structure and appearance. It is the easiest type for data capture, because
every data field is located at the same place for all documents.[citation needed]
Semi-structured documents (invoices, purchase orders, waybills, etc.) have the same structure
but their appearance depends on number of items and other parameters. Capturing data from
these documents is a complex, but solvable task.[citation needed]
Unstructured documents (letters, contracts, articles, etc.) could be flexible with structure and
appearance.
Developer
Basic
Technologies
Data Capture Application Data Capture SDK
ABBYY
OCR (195
languages),
ICR (113
languages),
OMR, OBR,
ABBYY FlexiCapture is an
intelligent data and
document capture software
that delivers automated
processing of any type of
ABBYY FlexiCapture Engine is
a data and document capture
SDK for any type of
structured, semi-structured
and unstructured documents

3. BCR structured, semi-
structured and
unstructured documents
and forms
and forms
Accusoft
OCR (118
languages),
ICR (11
languages),
OMR, OBR
ImageGear for .NET is an
SDK that delivers fully
managed code for WinForms,
ASP.NET, and WPF application
development. Optional
Recognition component enables
a comprehensive integrated
OCR toolkit.
FormSuite, available for .NET
or ActiveX, is a structured
forms processing SDK designed
to handle forms processing from
scanning to recognition.
Barcode recognition and
creation can also be added.
AnyDoc
Software
OCR (4
languages),
ICR, OMR,
OBR
OCR for AnyDoc automates
data capture from all
business documents,
including structured, semi-
structured, and
unstructured documents
by incorporating AnyApp
Technology for template-
free processing.
Cvision
Technologies
OCR (60
languages),
ICR (60
languages),
OMR, OBR
Cvision's Trapeze is an
intelligent software that is
able to recognize and
capture text from
structured, semi-
structured, and
unstructured documents
including forms, invoices,
and EOBs
Cvision's Trapeze's SDK
captures data from structured,
semi-structured, and
unstructured documents
including forms, invoices, and
EOBs
Expervision
OCR (18
languages),
ICR (18
languages),
OMR, OBR,
BCR
Expervision TypeReader
Expervision TypeReader can
automatically process full
text documents. In under the
premise of accurately
identification, its processing
speed can reach above 100
Expervision OpenRTK Engine is
an intelligent capture data and
document processing SDK. It
has flexible language support
function, in theory, it can
support additional anyone
language and train the engine to

4. pages each minute. adapt various fonts according to
customize demand. Customized
API definition and development
are supported.
I.R.I.S. Group
OCR (120
languages),
ICR (Latin
based
languages),
OMR, OBR,
BCR
IRISCapture for Invoices –
invoice processing solution
IRISCapture Pro for Forms
is an intelligent software
suite that automatically
captures, sorts and identifies
all types of documents and
forms
LEADTOOLS
OCR (118
languages),
ICR (15
languages),
OMR, OBR,
BCR
LEADTOOLS Forms
Recognition module is a .NET
SDK that harnesses the power of
LEAD's image processing
technology to intelligently
identify form components and
features that can be used to
recognize structured forms
Nuance
Communications
OCR (120
languages),
ICR, OMR,
OBR, BCR
OmniPage Professional 17
makes structured forms
made easy from start to
finish. You can turn paper
forms into electronic forms
and then collect the data.
OmniPage Capture SDK for
Windows with its advanced
Logical Form Recognition
(LFR) automates form template
creation and structured forms
processing.
PSIGEN
Software
OCR (99
languages),
ICR, OMR,
OBR, BCR
(1D and 2D)
PSI:Capture is a complete
capture solution that
includes all the functionlity
required to automatically
process all structured and
semi-structured documents,
including invoices, forms
and general mail. One of its
key strengths is its
unrivalled dynamic interface
to SharePoint.
The Internet and the future
The idea is as simple as its application is difficult. If all cans, books, shoes or parts of cars are
equipped with minuscule identifying devices, daily life on our planet will undergo a
transformation. Things like running out of stock or wasted products will no longer exist as we

5. will know exactly what is being consumed on the other side of the globe. Theft will be a thing of
the past as we will know where a product is at all times. Counterfeiting of critical or costly items
such as drugs, repair parts, or electronic components will be reduced or eliminated because
manufacturers or other supply chain entities will know where their products are at all times.
Product wastage or spoilage will be reduced because environmental sensors will alert suppliers
or consumers when sensitive products are exposed to excessive heat, cold, vibration, or other
risks. Supply chains will operate far more efficiently because suppliers will ship only the
products needed when and where they are needed. Consumer and supplier prices should also
drop accordingly.[1]
The global association Auto-ID Center was founded in 1999 and is made up of 100 of the largest
companies in the world such as Wal-Mart, Coca-Cola, Gillette, Johnson & Johnson, Pfizer,
Procter & Gamble, Unilever, UPS, companies working in the sector of technology such as SAP,
Aliens, Sun as well as five academic research centers.[2]
These are based at the following
Universities; MIT in the USA, Cambridge University in the UK, the University of Adelaide in
Australia, Keio University in Japan and University of St. Gallen in Switzerland.
The Auto-ID Center suggests a concept of a future supply chain that is based on the Internet of
objects, i.e. a global application of RFID. They try to harmonize technology, processes and
organization. Research is focused on miniaturization (aiming for a size of 0.3 mm/chip),
reduction in the price per single device (aiming at around $0.05 per unit), the development of
innovative application such as payment without any physical contact (Sony/Philips), domotics
(clothes equipped with radio tags and intelligent washing machines) and, last but not least,
sporting events (timing at the Berlin marathon).
AIDC 100
AIDC 100 is a professional organization for the automatic identification and data capture
(AIDC) industry. This group is composed of individuals who made substantial contributions to
the advancement of the industry. Increasing business's understanding of AIDC processes and
technologies are the primary goals of the organization.[3]
See also
Auto-ID Labs
Device management
Field Service Management
Mobile Enterprise
Mobile Asset Management
Ubiquitous computing
Ubiquitous Commerce
Digital Mailroom
References

6. 1. ^ Waldner, Jean-Baptiste (2008). Nanocomputers and Swarm Intelligence. London: ISTE
John Wiley & Sons. pp. 205–214. ISBN 1-84704-002-0.
2. ^ Auto-ID Center. "The New Network". Retrieved 23 June 2011.
3. ^ "AIDC 100". AIDC 100: Professionals Who Excel in Serving the AIDC Industry.
Archived from the original on 24 July 2011. Retrieved 2 August 2011.
Categories:
Automatic identification and data capture
Encodings
Multimodal interaction
Human–computer interaction
Radio-frequency identification
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