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利用不同尺度下复杂性的差异区分文字和照片

Image Classification Using Lempel-Ziv Complexity Difference at Different Scale

  • 摘要: 将信号分成多个区域,给予“0”,“1”新的定义,计算不同尺度下的复杂性而不增加符号数目.对文字图像和照片的分析显示,随着尺度的减小,照片复杂性增大的幅度大于文字.该结果说明:不同尺度下复杂性的差异可以作为图像分类的新方法或者作为现有分类器的特征.

     

    Abstract: In this paper we propose a method by dividing the original signal to multiple parts and assign new meaning to "1" and "0", to calculate Lempel-Ziv complexity at multi-scale without increasing the number of symbols. This new approach is presented for distinguishing textual images from pictorial images and we find that the complexity of pictorial images have more significant increase than that of textual images when the calculation scale becomes small. The test shows that multi-scale Lempel-Ziv complexity can be used as an image classification method or as a feature of image classifier.

     

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