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  • 标题:Image Classification using Statistical Learning Methods
  • 本地全文:下载
  • 作者:Jassem Mtimet ; Hamid Amiri
  • 期刊名称:Journal of Software Engineering and Applications
  • 印刷版ISSN:1945-3116
  • 电子版ISSN:1945-3124
  • 出版年度:2012
  • 卷号:5
  • 期号:12B
  • 页码:200-203
  • DOI:10.4236/jsea.2012.512B038
  • 出版社:Scientific Research Publishing
  • 摘要:In general, digital images can be classified into photographs, textual and mixed documents. This taxonomy is very useful in many applications, such as archiving task. However, there are no effective methods to perform this classification automatically. In this paper, we present a method for classifying and archiving document into the following semantic classes: photographs, textual and mixed documents. Our method is based on combining low-level image features, such as mean, Standard deviation, Skewness. Both the Decision Tree and Neuronal Network Classifiers are used for classification task.
  • 关键词:Image classification; Decision Tree; Neuronal Network; statistical analysis
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