Ontology type: schema:ScholarlyArticle
2000-08
AUTHORSXiaoyan Zhu, Yu Hao, Yifan Shi, Song Wang
ABSTRACT. Segmentation is the most difficult problem in handwritten character recognition systems and often causes major errors in performance. To reach a balance between speed and accuracy, a filter distinguishing connected images from isolated images for multiple stage segmentation is required. The Fourier spectrum is a promising approach to this problem, although it suffers from the heavy influence of stroke width. Therefore, we introduce SFS (SFS) to eliminate the stroke-width effect. Based on the SFS, a set of features and a fine-tuned criterion are presented to classify connected/isolated images. Theoretical analysis demonstrates their soundness, while experimental results demonstrate that this criterion is better than other methods. More... »
PAGES27-33
http://scigraph.springernature.com/pub.10.1007/pl00013550
DOIhttp://dx.doi.org/10.1007/pl00013550
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