Local Feature Based Word Spotting in Handwritten Archive Documents

被引:0
|
作者
Czuni, Laszlo [1 ]
Kiss, Peter Jozsef [1 ]
Gal, Monika
Lipovits, Agnes
机构
[1] Univ Pannonia, Dept Elect Engn & Informat Syst, Veszprem, Hungary
关键词
D O I
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中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper we deal with a special case of archive handwritten text recognition when word spotting can be used effectively. We analyze the use of local feature descriptors and show that the Scale Invariant Feature Transform can be used efficiently despite the large variety of word shape, and the effects of different noises. We evaluate the performance on a database of 1638 word records segmented from an archive book and show that the proposed feature processing method can achieve over 80% hit rate. Different parameter settings and variations of the local feature descriptor are analyzed.
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收藏
页码:178 / 183
页数:6
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