On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey

By Rejean Plamondon, Sargur N. Srihari. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000

2,921 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/d12864a8acbab1830be755bfb9cb177e31ca5e20

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Citations in the corpus

Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks (2008, background): “Offline handwriting recognition is generally observed to be harder than online handwriting recognition [14].”
Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks (2007, background): “Handwriting recognition is traditionally divided into off-line and on-line recognition [12].”
Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes (2007, background): “Some prior handwriting recognition systems have also resampled stroke paths [21,29].”
Text-Independent Writer Identification and Verification Using Textural and Allographic Features (2007, background): “Writer identification is rooted in the older and broader domain of automatic handwriting recognition [1], [2].”
IAM-OnDB - an on-line English sentence database acquired from handwritten text on a whiteboard (2005, background): “The recognition of unconstrained handwritten text is still a great challenge although research in the area has started more than 30 years ago [1, 17, 22].”
Automatic Signature Verification: The State of the Art (2008, background): “Thus, the FAR evaluation is difficult and generally imprecise [259], [377].”
Lexicon-free handwritten word spotting using character HMMs (2012, background): “The automatic recognition of handwritten text images is an offline task that is considered to be harder than online recognition, where temporal information can be exploited [2].”
Handwritten Numeral Databases of Indian Scripts and Multistage Recognition of Mixed Numerals (2009, neutral): “Related surveys are found in [12], [13], [ 14 ], [15].”
Recognizing objects in adversarial clutter: breaking a visual CAPTCHA (2003, background): “Plamondon and Srihari [16] provide an extensive survey of this work.”
Word spotting for historical documents (2007, background): “In recent years, research in handwriting recognition [22] has advanced to a level that makes commercial applications (e.”
Agnostic Learning vs. Prior Knowledge Challenge (2007, neutral): “An alternative used in handwriting recognition is to model the dynamics of handwriting to extract relevant features from on-line data [5].”
Behavior of Machine Learning Algorithms in Adversarial Environments (2010, background): “…such as natural language processing [cf., Jurafsky and Martin, 2008], face detection [cf., Zhao et al., 2003], and handwriting recognition [cf., Plamondon and Srihari, 2000], they also have potentially far-reaching utility for many applications in security, networking, and large-scale systems…”
Bidirectional Language Model for Handwriting Recognition (2012, background): “The recognition of handwritten text is a very active research field among researchers on pattern recognition [12].”
A survey on off-line Cursive Word Recognition (2002, background): “The main development of the /eld took place in the last decade [ 1 ,2] and some commercial products, based on CWR, are yet running in real world applications [3,4].”
Recognition and retrieval of mathematical expressions (2011, background): “ument recognition, perhaps the most well-known example of post-processing is the use of dictionaries and n-grams to refine preliminary OCR results obtained for individual characters [107,115].”