OCR (Concept) - Revision history

Randallkinard at 16:41, 28 August 2024

2024-08-28T16:41:56Z

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Randallkinard: Randallkinard moved page OCR to OCR (Concept): new naming convention

2024-04-17T20:45:43Z

Randallkinard moved page OCR to OCR (Concept): new naming convention

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Dgreenwood: Removed redirect to OCR - 2023

2024-01-02T18:29:07Z

Removed redirect to OCR - 2023

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Rpatton: Redirected page to OCR - 2023

2023-10-27T13:23:10Z

Redirected page to OCR - 2023

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Dgreenwood at 17:57, 12 December 2022

2022-12-12T17:57:23Z

← Older revision		Revision as of 12:57, 12 December 2022
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	<!--		[[Category:Articles]]
			[[Category:Version 2.90]]

			<!--EDITOR'S NOTE
			This article doesn't really need "How Tos". However, it should link to other articles that do have "How Tos" (In other words, the "How To Create an OCR Profile" section belongs in the "OCR Profile" article)

	== How To ==		== How To ==

Dgreenwood: /* What is an OCR Engine? */

2022-02-28T15:09:46Z

What is an OCR Engine?

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	For more in depth information on how OCR Engines work, visit the [[OCR Engine]] article.		For more in depth information on how OCR Engines work, visit the [[OCR Engine]] article.

	The Transym 4 and Transym 5 OCR engines are included in Grooper's licensing. Transym OCR 4 provides highly accurate English-only OCR while Transym OCR 5 provides multi-language OCR for 28 different languages. Google's open source Tesseract engine is available in version 2.72 and beyond. ~~ABBY FineReader, Prime OCR, and~~ Azure OCR ~~are~~ also supported but ~~require separate installations and~~ separate licensing.		The Transym 4 and Transym 5 OCR engines are typically included in Grooper's licensing. Transym OCR 4 provides highly accurate English-only OCR while Transym OCR 5 provides multi-language OCR for 38 different languages. Google's open source Tesseract engine is available in version 2.72 and beyond. Microsoft's Azure OCR is also supported but requires separate licensing.

	=== Image Processing and OCR ===		=== Image Processing and OCR ===

Dgreenwood at 19:22, 27 October 2020

2020-10-27T19:22:14Z

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	[[File:What is ocr.png\|thumb]]		[[File:What is ocr.png\|thumb]]
			<onlyinclude>
	<blockquote style="font-size:14pt">		<blockquote style="font-size:14pt">
	OCR stands for Optical Character Recognition. It allows text from paper documents to be digitized, in order to be searched or edited by other software applications. OCR converts typed or printed text from digital images of physical documents into machine readable, encoded text		OCR stands for Optical Character Recognition. It allows text from paper documents to be digitized, in order to be searched or edited by other software applications. OCR converts typed or printed text from digital images of physical documents into machine readable, encoded text
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	The Grooper activity that performs OCR is [[Recognize]]. Including a Recognize step in your [[Batch Process]] will allow you to OCR image-based content.		The Grooper activity that performs OCR is [[Recognize]]. Including a Recognize step in your [[Batch Process]] will allow you to OCR image-based content.
			</onlyinclude>

	== About ==		== About ==

Dgreenwood at 16:25, 31 August 2020

2020-08-31T16:25:23Z

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	Once OCR is performed, Grooper will have a set of ''machine readable'' characters it can work with, instead of just a bunch of pixels. How do you know an invoice document is an invoice? A simple way could be locating the word "invoice" (or other text associated with the invoice). You, as a human, do this by looking at the ink on a page (or pixels for a digital document) and reading the word "invoice". Grooper does this by using a Data Extractor (and regular expression) to read the machine readable text for the page. OCR is how each page gets that machine readable text in order to model the document set and process it.		Once OCR is performed, Grooper will have a set of ''machine readable'' characters it can work with, instead of just a bunch of pixels. How do you know an invoice document is an invoice? A simple way could be locating the word "invoice" (or other text associated with the invoice). You, as a human, do this by looking at the ink on a page (or pixels for a digital document) and reading the word "invoice". Grooper does this by using a Data Extractor (and regular expression) to read the machine readable text for the page. OCR is how each page gets that machine readable text in order to model the document set and process it.

	=== The General Process ===		=== The General Process: How does Grooper OCR documents? ===

	In Grooper, OCR is performed by the Recognize activity, referencing an [[OCR Profile]] which contains all the settings to get the OCR results, including which [[OCR Engine]] is used. The OCR Profile also has settings to optionally process those results to increase the accuracy of the OCR Engine used. The general process of OCR'ing a document is as follows in Grooper:		In Grooper, OCR is performed by the Recognize activity, referencing an [[OCR Profile]] which contains all the settings to get the OCR results, including which [[OCR Engine]] is used. The OCR Profile also has settings to optionally process those results to increase the accuracy of the OCR Engine used. The general process of OCR'ing a document is as follows in Grooper:
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	{\|		{\|
	\|+The [[Recognize]] activity is handed the document image and performs OCR.		\|+The [[Recognize]] activity is handed the document image and performs OCR.
	\|[[File:Ocr ~~results 1~~.png\|border\|500px]]		\|[[File:Ocr-document.png\|border\|500px]]
	\|}		\|}
	\|valign=top\|		\|valign=top\|
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	{\|		{\|
	\|+The results are seen here in a text flow.		\|+The results are seen here in a text flow.
	\|[[File:Ocr ~~results~~ 2.png\|border\|500px]]		\|[[File:Ocr-text-2.png\|border\|500px]]
	\|}		\|}
	\|		\|
	{\|		{\|
	\|+The results are seen here in a "Layout View". Using the character positions and font sizes obtained during OCR, the results are overlaid where they are on the document.		\|+The results are seen here in a "Layout View". Using the character positions and font sizes obtained during OCR, the results are overlaid where they are on the document.
	\|[[File:Ocr ~~results 3~~.png\|border\|500px]]		\|[[File:Ocr-text-1.png\|border\|500px]]
	\|}		\|}
	\|}		\|}

Dgreenwood at 19:20, 10 August 2020

2020-08-10T19:20:58Z

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	=== OCR vs. Native Text ===		=== OCR vs. Native Text ===

	OCR gets text specifically from images, whether they were printed and scanned or imported from a digital source. However, what if the document created digitally and imported in its original digital form? Wouldn't it have been created on a computer, using machine readable text? Most likely, yes! If a form was created using a product like Adobe Acrobat and filled in using a computer, the text comprising the document and the filled fields is encoded within the document itself. This is called "Native Text". This text is already machine readable. So there is no reason to OCR the document. Instead, the native text is extracted via Grooper's native text extraction. Native text has a number of advantages over OCR. OCR is not perfect. As you will see, OCR is a fairly complicated process with a number of opportunities to misread a document. Grooper has plenty of advancements to get around these errors and produce a better result, but OCR will rarely be as accurate as the original native text from a digital document.		OCR gets text specifically from images, whether they were printed and scanned or imported from a digital source. However, what if the document was created digitally and imported in its original digital form? Wouldn't it have been created on a computer, using machine readable text? Most likely, yes! If a form was created using a product like Adobe Acrobat and filled in using a computer, the text comprising the document and the filled fields is encoded within the document itself. This is called "Native Text". This text is already machine readable. So there is no reason to OCR the document. Instead, the native text is extracted via Grooper's native text extraction. Native text has a number of advantages over OCR. OCR is not perfect. As you will see, OCR is a fairly complicated process with a number of opportunities to misread a document. Grooper has plenty of advancements to get around these errors and produce a better result, but OCR will rarely be as accurate as the original native text from a digital document.

	However, be careful. Just because a PDF document has machine readable text behind it, does not mean that text is native text. If the document was OCR'd by a different platform, the text may have been inserted into the PDF (Grooper also has this capability upon exporting document). In these cases, we still recommend OCR'ing the document to take advantage of Grooper's superior OCR capabilities and get a more accurate result.		However, be careful. Just because a PDF document has machine readable text behind it, does not mean that text is native text. If the document was OCR'd by a different platform, the text may have been inserted into the PDF (Grooper also has this capability upon exporting document). In these cases, we still recommend OCR'ing the document to take advantage of Grooper's superior OCR capabilities and get a more accurate result.

Dgreenwood at 19:12, 14 July 2020

2020-07-14T19:12:45Z

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