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dc.contributor.authorHan Chin-Chuanen_US
dc.contributor.authorChen Ying-Nongen_US
dc.date.accessioned2014-12-16T06:14:17Z-
dc.date.available2014-12-16T06:14:17Z-
dc.date.issued2011-11-08en_US
dc.identifier.govdocG06K009/00zh_TW
dc.identifier.govdocG06K009/62zh_TW
dc.identifier.urihttp://hdl.handle.net/11536/104632-
dc.description.abstractThe present invention discloses an object image detection method, which uses a coarse-to-fine strategy to detect objects. The method of the present invention comprises steps: acquiring an image and pre-processing the image to achieve dimensional reduction and information fusion; using a trained filter to screen features; and sequentially using a coarse-level MLP verifier and a fine-level MLP verifier to perform a neural network image detection to determine whether the features of the image match the features of the image of a target object. The present invention simultaneously uses three mainstream image detection methods, including the statistic method, neural network method and adaboost method, to perform image detection. Therefore, the present invention has the advantages of the rapidity of the adaboost method and the accuracy of the neural network method at the same time.zh_TW
dc.language.isozh_TWen_US
dc.titleObject image detection methodzh_TW
dc.typePatentsen_US
dc.citation.patentcountryUSAzh_TW
dc.citation.patentnumber08055018zh_TW
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