Editing Handwriting recognition (section)

==Online recognition ==
Online handwriting recognition involves the automatic conversion of text as it is written on a special [[digitizer]] or [[Personal digital assistant|PDA]], where a sensor picks up the pen-tip movements as well as pen-up/pen-down switching. This kind of data is known as digital ink and can be regarded as a digital representation of handwriting. The obtained signal is converted into letter codes that are usable within computer and text-processing applications.

The elements of an online handwriting recognition interface typically include:

* a pen or stylus for the user to write with
* a touch sensitive surface, which may be integrated with, or adjacent to, an output display.
* a software application which interprets the movements of the stylus across the writing surface, translating the resulting strokes into digital text.

The process of online handwriting recognition can be broken down into a few general steps:

* preprocessing, 
* feature extraction and 
* classification

The purpose of preprocessing is to discard irrelevant information in the input data, that can negatively affect the recognition.<ref>Huang, B.; Zhang, Y. and Kechadi, M.; ''Preprocessing Techniques for Online Handwriting Recognition. Intelligent Text Categorization and Clustering'', Springer Berlin Heidelberg, 2009, Vol. 164, "Studies in Computational Intelligence" pp. 25–45.</ref> This concerns speed and accuracy. Preprocessing usually consists of binarization, normalization, sampling, smoothing and denoising.<ref>Holzinger, A.; Stocker, C.; Peischl, B. and Simonic, K.-M.; ''[http://www.mdpi.com/1099-4300/14/11/2324 On Using Entropy for Enhancing Handwriting Preprocessing]'', Entropy 2012, 14, pp. 2324–2350.</ref> The second step is feature extraction. Out of the two- or higher-dimensional vector field received from the preprocessing algorithms, higher-dimensional data is extracted. The purpose of this step is to highlight important information for the recognition model. This data may include information like pen pressure, velocity or the changes of writing direction. The last big step is classification. In this step, various models are used to map the extracted features to different classes and thus identifying the characters or words the features represent.

=== Hardware ===
Commercial products incorporating handwriting recognition as a replacement for keyboard input were introduced in the early 1980s. Examples include handwriting terminals such as the [[Pencept]] Penpad<ref>{{Citation
  | title = Pencept Penpad (TM) 200 Product Literature
  | publisher= Pencept, Inc.
  | date=1982-08-15
  | url=http://users.erols.com/rwservices/pens/biblio83.html#Pencept83
  }}</ref> 
and the Inforite point-of-sale terminal.<ref>{{Citation
  | title = Inforite Hand Character Recognition Terminal
  | publisher= Cadre Systems Limited, England
  | date=1982-08-15
  | url=http://users.erols.com/rwservices/pens/biblio83.html#Inforite82
  }}</ref>
With the advent of the large consumer market for personal computers, several commercial products were introduced to replace the keyboard and mouse on a personal computer with a single pointing/handwriting system, such as those from Pencept,<ref name="users.erols.com">{{Citation
  | title = Users Manual for Penpad 320
  | publisher= Pencept, Inc.
  | date=1984-06-15
  | url=http://users.erols.com/rwservices/pens/biblio85.html#Pencept84d
  }}</ref> CIC<ref name="rwservices.no-ip.info">{{Citation
  | title = Handwriter (R) GrafText (TM) System Model GT-5000
  | publisher= Communication Intelligence Corporation
  | date=1985-01-15
  | url=http://users.erols.com/rwservices/pens/biblio85.html#CIC85
  }}</ref> and others.
The first commercially available tablet-type portable computer was the [[Linus Write-Top|Write-Top]] from Linus Technologies, released in July 1988. Its operating system was based on [[MS-DOS]].<ref name=computer>{{cite book | last=Atkinson | first=Paul | date=2010 | url=https://books.google.com/books?id=D5H_OsxEywwC | title=Computer | publisher=Reaktion Books | pages=115–116 | isbn=9781861897374 | via=Google Books}}</ref><ref>{{cite book | last=Delbourg-Delphis | first=Marylène | date=2024 | url=https://books.google.com/books?id=g2z8EAAAQBAJ | title=Beyond Eureka!: The Rocky Roads to Innovating | publisher=Georgetown University Press | page=168 | isbn=9781647124229 | via=Google Books}}</ref>

In the early 1990s, hardware makers including [[NCR Corporation|NCR]], [[IBM]] and [[EO Personal Communicator|EO]] released [[tablet computer]]s running the [[PenPoint OS|PenPoint]] operating system developed by [[GO Corp.]] PenPoint used handwriting recognition and gestures throughout and provided the facilities to third-party software. IBM's tablet computer was the first to use the [[ThinkPad]] name and used IBM's handwriting recognition.  This recognition system was later ported to Microsoft [[Windows for Pen Computing]], and IBM's [[Pen for OS/2]].  None of these were commercially successful.

Advancements in electronics allowed the computing power necessary for handwriting recognition to fit into a smaller form factor than tablet computers, and handwriting recognition is often used as an input method for hand-held [[Personal Digital Assistant|PDA]]s. The first PDA to provide written input was the [[Apple Newton]], which exposed the public to the advantage of a streamlined user interface. However, the device was not a commercial success, owing to the unreliability of the software, which tried to learn a user's writing patterns.  By the time of the release of the [[Newton OS]] 2.0, wherein the handwriting recognition was greatly improved, including unique features still not found in current recognition systems such as modeless error correction, the largely negative first impression had been made. After discontinuation of [[Apple Newton]], the feature was incorporated in Mac OS X 10.2 and later as [[Inkwell (Macintosh)|Inkwell]].

[[Palm, Inc.|Palm]] later launched a successful series of [[Personal Digital Assistant|PDA]]s based on the [[Graffiti (Palm OS)|Graffiti]] recognition system. Graffiti improved usability by defining a set of "unistrokes", or one-stroke forms, for each character. This narrowed the possibility for erroneous input, although memorization of the stroke patterns did increase the learning curve for the user.  The Graffiti handwriting recognition was found to infringe on a patent held by Xerox, and Palm replaced Graffiti with a licensed version of the CIC handwriting recognition which, while also supporting unistroke forms, pre-dated the Xerox patent.  The court finding of infringement was reversed on appeal, and then reversed again on a later appeal.  The parties involved subsequently negotiated a settlement concerning this and other patents.

A [[Tablet computer|Tablet PC]] is a notebook computer with a [[Graphics tablet|digitizer tablet]] and a stylus, which allows a user to handwrite text on the unit's screen. The operating system recognizes the handwriting and converts it into text. [[Windows Vista]] and [[Windows 7]] include personalization features that learn a user's writing patterns or vocabulary for English, Japanese, Chinese Traditional, Chinese Simplified and Korean. The features include a "personalization wizard" that prompts for samples of a user's handwriting and uses them to retrain the system for higher accuracy recognition. This system is distinct from the less advanced handwriting recognition system employed in its [[Windows Mobile]] OS for PDAs.

Although handwriting recognition is an input form that the public has become accustomed to, it has not achieved widespread use in either desktop computers or laptops. It is still generally accepted that [[Alphanumeric keyboard|keyboard]] input is both faster and more reliable.  {{As of|2006}}, many PDAs offer handwriting input, sometimes even accepting natural cursive handwriting, but accuracy is still a problem, and some people still find even a simple [[virtual keyboard|on-screen keyboard]] more efficient.

===Software===
Early software could understand print handwriting where the characters were separated; however, cursive handwriting with connected characters presented [[Sayre's paradox|Sayre's Paradox]], a difficulty involving character segmentation. In 1962 [[Guberman Shelia (Shelija)|Shelia Guberman]], then in Moscow, wrote the first applied pattern recognition program.<ref>Guberman is the inventor of the handwriting recognition technology used today by Microsoft in Windows CE. Source: [https://www.iqt.org/in-q-tel-invests-in-pixlogic/ In-Q-Tel communication, June 3, 2003]</ref> Commercial examples came from companies such as Communications Intelligence Corporation and IBM.

In the early 1990s, two companies&nbsp;&ndash; ParaGraph International and Lexicus&nbsp;&ndash; came up with systems that could understand cursive handwriting recognition. ParaGraph was based in Russia and founded by computer scientist [[Stepan Pachikov]] while Lexicus was founded by [[Ronjon Nag]] and Chris Kortge who were students at Stanford University. The ParaGraph CalliGrapher system was deployed in the Apple Newton systems, and Lexicus Longhand system was made available commercially for the PenPoint and Windows operating system. Lexicus was acquired by Motorola in 1993 and went on to develop Chinese handwriting recognition and [[predictive text]] systems for Motorola. ParaGraph was acquired in 1997 by SGI and its handwriting recognition team formed a P&I division, later acquired from SGI by [[Vadem]]. Microsoft has acquired CalliGrapher handwriting recognition and other digital ink technologies developed by P&I from Vadem in 1999.

Wolfram Mathematica (8.0 or later) also provides a handwriting or text recognition function TextRecognize.