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Terminology Categories

13Sep

Unstructured Forms

Written by Ken Kramer. Posted in Scanning and Capture, Terminology

Unlike structured forms, unstructured forms have no specific layout and can vary widely.  In this type of forms processing, it becomes necessary to use several advanced capture technologies for sufficient data extraction accuracy and overall success in processing documents.  Here are some of the technologies leveraged in unstructured forms processing:

  • Full Page OCR – Converting the entire image to text provides a solid data set for the extraction engine to do its work.
  • Data Extraction – unstructured processing requires a pattern matching engine to identify and locate text patterns, and then extract the entire data set, a subset or nearby data.
  • Validation – extraction engines usually use pattern validation to insure accuracy.

Probably the best example of unstructured documents would be AP invoices.   Invoice processing is an extremely complex process that requires high levels of flexibility and accuracy in any forms processing engine.  Along with invoice header information, most engines also allow the extraction of the invoice line items, or the table of information.

See our Structured Forms Capture Solution

13Sep

Structured Forms

Written by Ken Kramer. Posted in Scanning and Capture, Terminology

Structured forms are documents that can be processed through the use of templates when performing document capture through import or scanning.  This type of structured document has the data elements in the same, or repeatable, areas of the page.  An example might be a DMV form that has a last name area that occurs at the same coordinates on a page.  Structured documents or forms are typically processing through the following advanced capture features:

  • Zone OCR – zoning is the best technology to extract structured data.  Through the creation of zones on a page, optical character recognition can repeatedly identify and extract information.
  • Anchoring – due to heavy use of zone OCR, page anchors must be in place to insure the zones register correctly on the page.
  • Image processing – structured forms typically have heavy lines on the page, and most technologies removed these lines before performing OCR to increase accuracy.

Structured forms processing also utilizes Optical Mark Recognition (OMR) for check boxes, and Intelligent Character Recognition (ICR) to read hand printed, structured forms.  Unstructured forms have data that changes location on the page, and require a different set of technology for accuracy and success.

See our Unstructured Forms Capture Solution

09Sep

Line Item Extraction

Written by Ken Kramer. Posted in Scanning and Capture, Terminology

Line Item Extraction, or table extraction, is a key feature in accounts payable invoice automation and processing.   Similar to header extraction,  invoice line item extraction finds the table of items on the invoice page, examines the table headers, and then proceeds to extract the invoice rows and columns.  It uses Optical Character Recognition (OCR) technology to convert the scanned image to text, and then leverages both pattern matching and location information to pull out the data.  Along with the invoice header, this information can then be compared to the accounting system to insure proper billing and payment.   This extraction method provides an amazing return on investment for any AP solution, as the manual keying and entry of invoice data is tedious and time consuming for any accounting department.

 

See our AP/Invoice Extraction Solutions

09Sep

Header Extraction

Written by Ken Kramer. Posted in Scanning and Capture, Terminology

When processing invoices for AP automation, header extraction is the process of using Optical Character Recognition (OCR) to extract the key data in the top area, or header, of the invoice.   Usually, the OCR is combined with a pattern matching, or key-value, extraction method that finds specific terms and extracts the information that follows. Below is typical information deemed the header:

  • Invoice Number
  • Invoice Date
  • Vendor Name
  • PO Number
  • Terms

This identifying information is used as critical information when integrating with an ERP or Accounting System.  The other type of extraction when it comes to invoice processing is line item extraction.  The chief goal of automated extraction is to reduce manual keying of information through automation and validation.  This adds to efficiency and reduced costs.

 

See our AP Invoice Data Extraction Solutions

07Sep

Invoice Processing

Written by Ken Kramer. Posted in Scanning and Capture, Terminology

Invoice processing is a digital transformation solution that provides the means to scan incoming invoices, separate documents with classification and extract invoice header and line item information.  The final result is data transfer to an accounting system and a reduction in overall time and labor to process payment.  The system typically combines several pieces of software, including: document capture and scanning, workflow/BPM and a document management system.

Typically, invoices are scanned when they enter the organization in the accounts payable department.  The scanned documents go through a document classification system, information is extracted, and operators review the results.  From there, depending on the organization, invoices can be routed for approvals through workflow, or can be placed in an end repository or DMS for archival and retrieval purposes.

Invoice processing and AP solutions are key focal points for any organization looking to transform and eliminate the flow of paper.  It is a labor intensive process, and involves the manual keying of information, labor intensive checking of accounting systems and review for errors in billing.

 
See our Invoice Processing Solutions

07Sep

AP Automation

Written by Ken Kramer. Posted in Scanning and Capture, Terminology

AP Automation is a solution or series of solutions that helps organizations automate the processing of inbound invoices.   Invoice processing is one of the most paper intensive processes within any organization, and depending on the size of the company, accounts payable departments can be totally inundated with paper.   AP Automation and Invoice processing solutions can be a combination of software and hardware to provide the following:

  • Scanning and capture of invoice documents and data
  • Facilitation of approvals through AP workflow
  • Archive and routing of invoices with a document management system

By creating a digital invoice process, companies can glean the following benefits:

  • Decrease costs and personnel required in AP departments
  • Eliminate the routing of paper
  • Take advantage of early pay discounts
  • Quickly identify errors

 

See our AP Invoice Solutions

03Sep

Image Processing

Written by Ken Kramer. Posted in Scanning and Capture, Terminology

Image processing is a feature within document capture software that provides the ability to normalize and “clean” incoming scanned documents and images.  Below are examples of image processing components:

  • Despeckle
  • Deskew
  • Rotate
  • Deshade
  • 3 Hole Punch Removal
  • Border removal

Image processing provides the ability to improve the image quality and remove noise, which is critical for accuracy in OCR, ICR and OMR.  It also insures the long term viability of an archived document.  Most document capture programs have the ability to improve image quality, and many of the document scanners on the market will perform image “cleanup” as part of the scanning or imaging process.  Many provide the ability to create profiles for specific types of documents, depending on the end goal, and quality of the original documents.  Companies like Ephesoft and Fujitsu have built their own image processing software that automates the cleanup, and gives you the highest quality image without intervention.

 

Read more on our Image Processing Solution

03Sep

Document Type

Written by Ken Kramer. Posted in Document Management & Enterprise Content Management, Scanning and Capture, Terminology

A document type is a defined template within a document management or document capture application.   This template establishes the properties, behavior and characteristics of a specific type of entity within the system, including but not limited to:

  • Index Fields
  • Workflow
  • OCR requirements
  • Security
  • Classification

Really it is a set of controlling rules on how users can process and interact with information.  An example set of document types might be: invoices, purchase orders, credit memos, contracts, email and agreements.  Each would have their own independent properties to help users find them within the confines of the document management system.   In an advanced capture system, document types establish processing parameters, as well as the data to be extracted, and how it is ultimately extracted.

03Sep

Index Fields

Written by Ken Kramer. Posted in Document Management & Enterprise Content Management, Scanning and Capture, Terminology

An Index Field is a piece of data associated with a document or set of documents in a document management system.  These fields can be assigned prior to the document being placed within the system, through the use of a front end document capture application, or can be direct indexed while in the repository.  The process, called indexing, can be manual or can be fully automated through the use of other technologies like OCR, OMR and ICR .  Index fields are usually mapped to a particular type of data that corresponds to a database, and include text, currency, integers and memo type information.   Many organizations have outsourced this process of indexing to document scanning service bureaus, or business process outsourcing companies due to its intense time demands.  The term “index fields” varies, depending on the type of system being utilized, and can also be called metadata fields, columns (in SharePoint) or many other names.  The primary purpose of these fields is to establish search criteria and filtering capability when searching for documents within the system.   Here are some general criteria when establishing index structure for a particular type of document:

  • Limit it to 5 fields – anymore than 5 fields is overkill, and adds unecessary time to the indexing process.
  • Utilize a Date – date ranges are common search criteria, and allows for complex searches required in audits and legal cases.
  • Use a unique identifier – although many types of documents do not have a single unique ID, try to establish a field that can ID that exact document.  An example might be a contract number, or an invoice number in AP invoice processing.
02Sep

Zone OCR

Written by Ken Kramer. Posted in Scanning and Capture, Terminology

Zone OCR, or Optical Character Recognition, is a process by which a specific area on a scanned or imported document image is converted to text.  Zoning, as it is called, is leveraged to automate data entry by mapping areas on a page to index fields.   Straight zone OCR can be problematic due to a number of issues inherent to capturing documents:

  • Page Registration – page registration is the shifting of document page images due to slight differences in scanning hardware.   A minor shift in the image left or right can render zone OCR useless.
  • Image Quality – low image quality can provide inaccurate results.  Shading, speckling, contrast and brightness are just a few of the image problems that can affect the conversion of image to text.
  • Form Changes – in forms processing, Zone OCR usually leverages a fixed image template for areas on a page.  Any revision or change in the layout of the form can make zone OCR ineffective.

There are several enhanced zone OCR features that can alleviate these issues, including: image cleanup or processing, page anchoring and zone pattern matching.