Online writing-box-free recognition of handwritten Japanese text considering character size variations

Fukushima, Tomihiro; Nakagawa, Masaki

doi:10.1109/icpr.2000.906087

Cited by 18 publications

(15 citation statements)

References 2 publications

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“…To search for the best alignment, each path is evaluated by a cost function. Inspired by [11][12], we define the alignment cost as a weighted sum:…”

Section: Problem Formulationmentioning

confidence: 99%

“…Geometric context has been used in handwriting recognition to reduce character segmentation and recognition errors, by using various geometric features (such as character size, inter-character and betweencharacter gaps) and statistical models (geometric class means, Gaussian density models, discriminative classifiers, etc.) for handwritten word and Japanese character string recognition [9][10][11][12][13]. These methods cannot be used straightforwardly for Chinese handwriting due to its greater challenge.…”

Section: Introductionmentioning

confidence: 99%

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Integrating Geometric Context for Text Alignment of Handwritten Chinese Documents

Yin

Wang

Liu

2010

2010 12th International Conference on Frontiers in Handwriting Recognition

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“…To search for the best alignment, each path is evaluated by a cost function. Inspired by [11][12], we define the alignment cost as a weighted sum:…”

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrating Geometric Context for Text Alignment of Handwritten Chinese Documents

Yin

Wang

Liu

2010

2010 12th International Conference on Frontiers in Handwriting Recognition

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“…Most previous publications and systems assumed only horizontal lines of text [46][47], while we attempted to relinquish any writing constraint from online text input. We proposed a method to recognize mixtures of horizontal, vertical, and slanted lines of text with assuming normal character orientation [48].…”

Section: Problemsmentioning

confidence: 99%

Recent Results of Online Japanese Handwriting Recognition and Its Applications

Nakagawa

Tokuno

Zhu

et al.

Arabic and Chinese Handwriting Recognition

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Abstract. This paper discusses online handwriting recognition of Japanese characters, a mixture of ideographic characters (Kanji) of Chinese origin, and the phonetic characters made from them. Most Kanji character patterns are composed of multiple subpatterns, called radicals, which are shared among many (sometimes hundreds of) Kanji character patterns. This is common in Oriental languages of Chinese origin, i.e., Chinese, Korean and Japanese. It is also common that each language has thousands of characters. Given these characteristics, structured character pattern representation (SCPR) composed of subpatterns is effective in terms of the size reduction of a prototype dictionary (a set of prototype patterns) and the robustness to deformation of common subpatterns. In this paper, we show a prototype learning algorithm and HMM-based recognition for SCPR. Then, we combine the SCPR-based online recognizer with a compact offline recognizer employing quadratic discriminant functions. Moreover, we also discuss online handwritten Japanese text recognition and propose character orientation-free and line direction-free handwritten text recognition and segmentation. Finally, as applications of online handwritten Japanese text recognition, we show segmentation of mixed objects of text, formulas, tables and line-drawings, and handwritten text search.

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“…Most of the previous publications and systems have been assuming only horizontal lines of text [4,5,6] while we have been trying to relinquish any writing constraint from on-line text input. We proposed a method to recognize mixtures of horizontal, vertical and slanted lines of text with assuming normal character orientation [7], but left handwriting recognition with characters are also rotated like handwritings often made on whiteboards.…”

Section: Introductionmentioning

confidence: 99%

“…Not only a single character recognition with a writing box or frame imposed for each character, handwritten text recognition without writing boxes or frames (writing-boxfree recognition) has been also needed, and our previous research [4] was employed into products. Further demand is conceived to recognize handwriting made on large surfaces by people.…”

Section: Introductionmentioning

confidence: 99%

Online handwritten Japanese text recognition free from constrains on line direction and character orientation

Nakagawa

Onuma

Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.

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This paper describes an on-line handwritten Japanese text recognition method that is liberated from constraints on writing direction (line direction) and character orientation. This method estimates the line direction and character orientation using the time sequence information of pen-tip coordinates and employs writingbox-free recognition with context processing combined. The method can cope with a mixture of vertical, horizontal and skewed lines with arbitrary character orientations. It is expected useful for tablet PC's, interactive electronic whiteboards and so on.

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Online writing-box-free recognition of handwritten Japanese text considering character size variations

Cited by 18 publications

References 2 publications

Integrating Geometric Context for Text Alignment of Handwritten Chinese Documents

Integrating Geometric Context for Text Alignment of Handwritten Chinese Documents

Recent Results of Online Japanese Handwriting Recognition and Its Applications

Online handwritten Japanese text recognition free from constrains on line direction and character orientation

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