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dc.contributor.author Li, Fangyi
dc.contributor.author Shen, Qiang
dc.contributor.author MacParthalain, Neil
dc.contributor.author Li, Ying
dc.date.accessioned 2016-09-22T10:36:14Z
dc.date.available 2016-09-22T10:36:14Z
dc.date.issued 2016-08-01
dc.identifier.citation Li , F , Shen , Q , MacParthalain , N & Li , Y 2016 , ' Handwritten Chinese character recognition using fuzzy image alignment ' Soft Computing , vol 20 , no. 8 , pp. 2939–2949 . DOI: 10.1007/s00500-015-1923-y en
dc.identifier.issn 1432-7643
dc.identifier.other PURE: 6741789
dc.identifier.other PURE UUID: d04ad472-49a3-4b5e-8f07-e757f02231b5
dc.identifier.other Scopus: 84947439820
dc.identifier.other handle.net: 2160/43600
dc.identifier.uri http://hdl.handle.net/2160/43600
dc.description.abstract The task of handwritten Chinese character recognition is one of the most challenging areas of human handwriting classification. The main reason for this is related to the writing system itself which encompasses thousands of characters, coupled with high levels of diversity in personal writing styles and attributes. Much of the existing work for both online and off-line handwritten Chinese character recognition has focused on methods which employ feature extraction and segmentation steps. The preprocessed data from these steps form the basis for the subsequent classification and recognition phases. This paper proposes an approach for handwritten Chinese character recognition and classification using only an image alignment technique and does not require the aforementioned steps. Rather than extracting features from the image, which often means building models from very large training data, the proposed method instead uses the mean image transformations as a basis for model building. The use of an image-only model means that no subjective tuning of the feature extraction is required. In addition by employing a fuzzy-entropy-based metric, the work also entails improved ability to model different types of uncertainty. The classifier is a simple distance-based nearest neighbour classification system based on template matching. The approach is applied to a publicly available real-world database of handwritten Chinese characters and demonstrates that it can achieve high classification accuracy and is robust in the presence of noise. en
dc.language.iso eng
dc.relation.ispartof Soft Computing en
dc.rights en
dc.subject handwritten Chinese character recognition en
dc.subject fuzzy entropy en
dc.subject group-wise image alignment en
dc.title Handwritten Chinese character recognition using fuzzy image alignment en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article en
dc.description.version publishersversion en
dc.identifier.doi https://doi.org/10.1007/s00500-015-1923-y
dc.contributor.institution Department of Computer Science en
dc.description.status Peer reviewed en


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