Motoki Onuma

A Model of On-line Handwritten Japanese Text Recognition Free from Line Direction and Writing Format Constraints

This paper presents a model and its effect for on-line handwritten Japanese text recognition free from line-direction constraint and writing format constraint such as character writing boxes or ruled lines. The model evaluates the likelihood composed of character segmentation, character recognition, character pattern structure and context. The likelihood of character pattern structure considers the plausible height, width and inner gaps within a character pattern that appear in Chinese characters composed of multiple radicals (subpatterns). The recognition system incorporating this model separates freely written text into text line elements, estimates the average character size of each element, hypothetically segments it into characters using geometric features, applies character recognition to segmented patterns and employs the model to search the text interpretation that maximizes likelihood as Japanese text. We show the effectiveness of the model through recognition experiments and clarify how the newly modeled factors in the likelihood affect the overall recognition rate.

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

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 writing-box-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 PCs, interactive electronic whiteboards and so on.

A search method for on-line handwritten text employing writing-box-free handwriting recognition

This paper presents a method for writing-box-free on-line handwritten text search. It searches for a target keyword in the lattice composed of candidate segmentations and candidate characters. By considering the accuracy of the recognition method and the length of the keyword, the method decreases noises to be output from the lattice effectively. When the keyword consists of three characters, we have achieved the recall rate 89.4%, the precision rate 93.2% and F measure 0.912.

A formalization of on-line handwritten Japanese text recognition free from line direction constraint

This work presents a formalization of an on-line writing-box free, line-direction free handwritten Japanese text recognition and its effect. By normalizing character orientation, even text of arbitrary character orientation can be recognized. The method evaluates the likelihood composed of character segmentation, character recognition, character pattern structure and context. The likelihood of character pattern structure considers the plausible height, width and gaps within a character pattern that appear in Chinese characters composed of multiple radicals (subpatterns). We show how the newly modeled factors in the likelihood affect the overall recognition rate.

Recent results of online Japanese handwriting recognition and its applications

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.

An On-line Handwritten Japanese Text Recognition System Free from Line Direction and Character Orientation Constraints

This paper describes an on-line handwritten Japanese text recognition system that is liberated from constraints on line direction and character orientation. The recognition system first separates freely written text into text line elements, second estimates the line direction and character orientation using the time sequence information of pen-tip coordinates, third hypothetically segment it into characters using geometric features and apply character recognition. The final step is to select the most plausible interpretation by evaluating the likelihood composed of character segmentation, character recognition, character pattern structure and context. The method can cope with a mixture of vertical, horizontal and skewed text lines with arbitrary character orientations. It is expected useful for tablet PCs, interactive electronic whiteboards and so on.