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{{Short description|Process of converting data from written forms into electronic format}}

{{Article issues|orphan =August 2009|wikify =August 2009}}

'''Forms processing''' is a process by which one can capture information entered into data fields and convert it into an electronic format. This can be done manually or automatically, but the general process is that [[hard copy]] data is filled out by humans and then "captured" from their respective fields and entered into a database or other electronic format.

==Overview==

Defining '''Forms Processing''' in simple terms, it is a process by which one can capture information entered into data fields and convert it into an electronic format.<br />

In the broadest sense, forms processing systems can range from athe processing of small application formforms to a large scale survey formforms with multiple pages. There are several common issues that are involved in forms processing when done manually. These are a lot of tedious human efforts put in, the data keyed in by the user may result in typos, and many hours of labor result from this lengthy process. If the forms are processed using [[computer software]] driven applications these common issues can be resolved and minimized to great extent. Most methods for forms processing address the following areas :<br />.

In this process:

*Entered data is “captured” from their respective fields;

*Forms themselves are digitized and saved as images.

What it means is that the [[hard copy]] of the data on the document can be scanned in as an image using a scanner. This image is then recognized based on a pre-defined configuration. The data is captured from particular zones and stored in an electronic format.

1. ==Manual data entry==

<br>'''Overview:'''<br>

This method of [[data processing]] involves human operators keying in data found on the form. The manual process of data entry has many disadvantages in speed, accuracy and cost. Based on average professional [[Data entry clerk|typist]] speeds of 50 to 80 wpm,<ref>{{Citation|author=Teresia R. Ostrach|year=1997|title=Typing Speed: How Fast is Average|url=http://onlinestudentreadiness.org/documents/TypingSpeed.pdf|archive-url=https://web.archive.org/web/20120502164156/http://onlinestudentreadiness.org/documents/TypingSpeed.pdf|archive-date=2012-05-02|url-status=dead}}</ref> one could generously estimate about two hundred pages per hour for forms with fifteen one-word fields (not counting the time for reading and sorting pages). In contrast, modern [[Image scanner#Document processing|commercial scanners]] can [[Document imaging|scan and digitize]] up to 200 pages per ''minute''.<ref>{{cite web | url = https://www.engadget.com/2006/11/03/kodak-intros-200-page-per-minute-i1860-commercial-scanner/ | title = Kodak intros 200 page-per-minute i1860 commercial scanner | access-date = 2011-11-04 | publisher = [[Engadget]]}}</ref> The second major disadvantage to manual data entry is the likelihood of [[typographical errors]]. When factoring in the cost of labor and working space, manual data entry is a very inefficient process.

In the broadest sense, forms processing systems can range from a small application form to a large scale survey form. There are several common issues that are involved in forms processing when done manually. These are a lot of tedious human efforts put in, the data keyed in by the user may result in typos, and many hours of labor result from this lengthy process. If the forms are processed using [[computer software]] driven applications these common issues can be resolved and minimized to great extent. Most methods for forms processing address the following areas :<br />

1. Manual data entry

==Automated forms processing==

2. Automatic form input system<br />

Manual data entry is theThis method of [[data processing]] where the data is keyed in by a human operator while Automatic Form Input System is that which can automate the data processing by using pre-defined templates and configurations. A template in this case, would be a ''map'' of the document, detailing where the data fields are located within the form or document.<br> As compared to the manual data entry process, automatic form input systems are preferable, since they help reduce the problems faced during manual data processing.

The manual process of data entry implies many opportunities for errors, such as delays in data capture, as every single data field has to be keyed in manually, a high amount of operator misprints or typos, high labor costs from the amount of manual labor required. Manual processing also implies higher labor expenses in regards to spending for equipment and supplies, rent, etc.

As compared to the manual data entry process, automatic form input systems are more preferable, as it helps in eliminating all the above mentioned problems faced during manual data processing.

Automatic form input systemsystems usesuse different types of recognition methods such as [[Opticaloptical character recognition|Optical Character Recognition]] (OCR) for machine print, Optical[[optical Markmark Recognitionrecognition|optical mark reading]] (OMR) for check/mark sense boxes, [[Barbar Codecode]] Recognitionrecognition (BCR) for barcodes, and [[Intelligentintelligent Charactercharacter Recognitionrecognition]] (ICR) for hand print. ICR accuracy depends on user hand writing patterns, but certain recognition engines have been designed specifically for this purpose.

With automated formsform inputprocessing system technology users are able to process documents from their scanned images into a [[Machine-readable data|computer readable]] format such as ANSI, XML, CSV, PDF or CSVinput directly into a database.

Forms Processing has developed beyond simplebasic capture of the data. Recognition of data using OCR/ICR/OMR/BCR will help capture data as an electronic format. Forms processing not only encompasses a recognition process but also helps manage the complete [[:wikt:life cycle|life cycle]] of documents which starts from scanning of the document to the extraction of the data, and often to delivery into a back-end system. In some cases it may also include processing or generating well formatedformatted results through calculations and analysis. An automated forms processing system can be valuable if there is a need to process hundreds or thousands of images every day.

=== First Step: Assessment of the form structure ===

'''Components:'''<br>

The first step in understanding automated forms processing is to analyze the type of form from which the extraction of data is desired. Forms can be classified as one of two high level categories for the purpose of extracting data. Four categories have been proposed<ref>{{Cite book|url=https://books.google.com/books?id=44arCAAAQBAJ&q=example+of+a+fixed+form+for+extraction&pg=PA425|title=Pattern Recognition and Machine Intelligence: 4th International Conference, PReMI 2011, Moscow, Russia, June 27 - July 1, 2011, Proceedings|last1=Kuznetsov|first1=Sergei O.|last2=Mandal|first2=Deba P.|last3=Kundu|first3=Malay K.|last4=Pal|first4=Sankar Kumar|date=2011-06-25|publisher=Springer|isbn=9783642217869|language=en}}</ref> however the document capture industry has settled up these two:

Various Components included in Data Processing using Automatic Form Input System include:<br />

# Fixed forms. This type of form is defined as one in which the data to be extracted is always found in the same absolute position on a page. This allows a type of lens grid to be applied to the document and every subsequent occurrence of this document in order to extract the data. An example of a fixed form is a typical credit application form.<ref>{{Cite web|url=http://www.bfma.org/resource/resmgr/articles/05_04.pdf|title=CAPTURING SEMI-STRUCTURED FORMS AND DOCUMENTS: CHALLENGES AND AVAILABLE TECHNOLOGIES|last=Vassylyev|first=Artur|date=10 June 2008|archive-url=https://web.archive.org/web/20170428144034/http://www.bfma.org/resource/resmgr/articles/05_04.pdf|archive-date=2017-04-28|url-status=dead|access-date=4 April 2017}}</ref>

1. OCR - Optical Character Recognition<br />

# Semi-structured (or unstructured) form. This form is one in which the ___location of the data and fields holding the data vary from document to document. This type of document is perhaps most easily defined by the fact that it is not a fixed form. In the document capture industry, a semi-structured form is also called an unstructured form. Examples of these types of forms include letters, contracts, and invoices. According to a study by AIIM, about 80% of the documents in an organization fall under the semi-structured definition.<ref>{{Cite web|url=https://www.aiim.org/pdfdocuments/MIWP_Forms-Processing_2012.pdf|title=Forms Processing- user experiences of text and handwriting recognition (OCR/ICR)|access-date=4 April 2017|archive-date=28 April 2017|archive-url=https://web.archive.org/web/20170428142430/http://www.aiim.org/pdfdocuments/MIWP_Forms-Processing_2012.pdf|url-status=dead}}</ref>

2. OMR - [http://www.omrhome.com Optical mark recognition|Optical Mark Recognition]<br />

Although the components (described below) used for the extraction of data from either type of form is the same the way in which these are applied varies considerably based upon the type of document.

3. ICR - Intelligent Character Recognition<br />

4. BCR - Barcode Recognition<br />

5. MICR - [[Magnetic ink character recognition|Magnetic Ink Character Recognition]]

'''===Components:'''<br>===

Optical Character Recognition (OCR) Recognizes machine-printed uppercase/lowercase alphabetic, numeric, accented characters, many [[Currency sign|currency symbols]], digits, arithmetic symbols, expanded punctuation characters and more.

Various components included in data processing using automatic form-input system include

#OCR – [[Optical character recognition]]

#OMR – [[Optical mark recognition]]

#ICR – [[Intelligent character recognition]]

#BCR – [[Barcode]] recognition

5. #MICR -– [[Magnetic ink character recognition|Magnetic Ink Character Recognition]]

Optical Character Recognition (OCR) Recognizesrecognizes machine-printed uppercase/lowercase alphabetic, numeric, accented characters, many [[Currency sign|currency symbols]], digits, arithmetic symbols, expanded punctuation characters and more.

Intelligent Character Recognition (ICR) Recognizes hand-printed American and [[European English]] characters using pre-defined character sets: uppercase, lowercase, [[mixed case]] alphabetic, digits, currency (including $ (dollar), ¢ (cent) € (Euro) £ (pound), ¥ (Yen)), arithmetic and punctuation characters (including period, comma, [[Quotation mark|single quote]], double quote, ! & ( ) ? @ { } \ # % * + - / : ; < = >)

Intelligent Character Recognition (ICR) Recognizesrecognizes hand-printed American and [[European English (disambiguation)|European English]] characters using pre-defined character sets: uppercase, lowercase, [[mixed case]] alphabetic, digits, currency (including $ (dollar), ¢ (cent) € (Euro) £ (pound), ¥ (Yen)), arithmetic and punctuation characters (including period, comma, [[Quotation mark|single quote]], double quote, ! & ( ) ? @ { } \ # % * + -– / : ; < = >)

Magnetic Ink Character Recognition (MICR) Recognition technology to facilitate the processing of the MICR fonts of Cheques. This minimizes chances of errors in clearing of Cheques. It is also useful for easier and faster transfer of funds. MICR provides a secure, high-speed method of scanning and processing information.

MagneticMICR Ink Character Recognition (MICR)is Recognitionrecognition technology to facilitate the processing of the MICR fonts of Chequescheques. This minimizes chances of errors in clearing of Chequescheques. It is also useful for easier and faster transfer of funds. MICR provides a secure, high-speed method of scanning and processing information.

Optical Mark Recognition (OMR) identifies bubbles filled in by hand or check boxes on printed forms. Usually OMR supports single and multiple mark recognition. The fields to be recognized can be specified as grids (rows by columns) or single bubbles.

Barcode Recognition can read more than 20 industry 1D and 2D barcodes including Code39, CODABAR, [[Interleaved 2 of 5]], Code93 and more. It automatically detects all barcodes in an image or specified area within the image.<br />

<br>'''Process:'''<br>

===Process===

The process of Automatedautomated Formsforms Processingprocessing typically includes the following steps:

1. A batch of completed forms is scanned using a high-speed scanner (usually scanners that scan at least 10 [[Computer printer|pages per minute]] are used); recommended scanners like Kodak, Canon and HP could be preferred.

#A batch of completed forms is scanned using a high-speed scanner

2. Most of the data are recognized automatically using the pre requisites;

#Images are cleaned with document image processing algorithms to improve accuracy

3. A few characters about which the program is uncertain are passed on to a human operator;

#Forms are classified based on original template forms and the fields are extracted using the appropriate recognition components

Verified data are saved into a database or exported as CSV or XML.

#Fields which the system flagged with a low confidence are queued for verification by a human operator

#Verified data areis saved into a database or exported to searchable text format such as CSV or, XML. or PDF

===Prerequisites===

Though automated forms processing has many great advantages over manual data entry, it still comes with some limitations. To achieve the best accuracy, some prerequisites should be followed.

1. #Scan Formatformat: It includes the format of scanned file, Resolution and DPI, Color Mode

2. #Configuration: The scanned image layout needs to be configured for this automation

3. #Recognition: The pre defined out put formats

4. #Result / Analyzeanalyze: Any specific format of result of capture value data presentation.

One very important consideration is indexing, determining the [[metadata]] that will be used to describe the data contained within the documents. This attribute perhaps drives the forms processing solution more than any other.

==External links==

{{wikiquote}}

* [https://web.archive.org/web/20100529053053/http://www.aiim.org.uk/industrywatch/surveys.asp AIIM market intelligence reports]

==References==

<br>'''Pre Requisites:'''<br>

{{reflist}}

The process of Automatic Forms Processing is of a great success if the pre requisites are successfully maintained.

Few of the pre requisites include:

1. Scan Format: It includes the format of scanned file, Resolution and DPI, Color Mode

2. Configuration: The scanned image layout needs to be configured for this automation

3. Recognition: The pre defined out put formats

4. Result / Analyze: Any specific format of result of capture value data presentation.

[[Category:Automatic identification and data capture]]