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Compared to human intelligence, computers are far short of common sense knowledge which people normally acquire during the formative years of their lives. This paper investigates the effects of employing common sense knowledge as a new linguistic context in handwritten Chinese text recognition. Three methods are introduced to supplement the standard n-gram language model: embedding model, direct model,...
We consider the problem of similar Chinese character recognition in this paper. Engaging the Average Symmetric Uncertainty (ASU) criterion to measure the correlation between different image regions and the class label, we manage to detect the most critical regions for each pair of similar characters. These critical regions are proved to contain more discriminative information and hence can largely...
To reduce the classification errors of online handwritten Japanese character recognition, we propose a method for confusing characters discrimination with little additional costs. After building confusing sets by cross validation using a baseline quadratic classifier, a logistic regression (LR) classifier is trained to discriminate the characters in each set. The LR classifier uses subspace features...
The hierarchical nature of Chinese characters has inspired radical-based recognition, but radical segmentation from characters remains a challenge. We previously proposed a radical-based approach for on-line handwritten Chinese character recognition, which incorporates character structure knowledge into integrated radical segmentation and recognition, and performs well on characters of left-right...
The alignment of text line images with text transcript is a crucial step of handwritten document annotation. Handwritten text alignment is prone to errors due to the difficulty of character segmentation and the variability of character shape, size and position. In this paper, we propose to incorporate the geometric context of character strings to improve the alignment accuracy for offline handwritten...
The splitting of touching characters remains a challenge in over-segmentation, which is crucial to the performance of integrated segmentation-recognition of handwritten character strings. In this paper, we propose a new method based on contour analysis for touching character splitting in Chinese handwriting. To reliably locate splitting points on the contour of touching pattern, we pair upper and...
This paper presents a radical-based on-line handwritten Chinese character recognition method, which integrates appearance-based radical recognition and geometric context into a principled framework using a character-radical dictionary to guide radical segmentation and recognition during path search. To solve the connection between radicals, we detect corner points to extract sub-strokes. Based on...
This paper describes an online handwritten Japanese character string recognition system based on conditional random fields, which integrates the information of character recognition, linguistic context and geometric context in a principled framework, and can effectively overcome the variable length of candidate segmentation. For geometric context, we employ both unary and binary feature functions,...
This paper describes an online handwritten Japanese character string recognition system integrating scores of geometric context, character recognition, and linguistic context. We give a string evaluation criterion for better integrating the multiple scores while overcoming the effect of string length variability. For measuring geometric context, we propose a statistical method for modeling both single-...
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