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Images Classifications Based on Color-Texture Feature

机译:基于颜色纹理特征的图像分类

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摘要

This paper puts forwards a method of using MGabor filter-banks to extract Texture-Color features from digital images, and then to construct a group of support vector machines (SVM) classifiers to automatically and accurately classify color digital images. Successful experiments are conducted on the Simplicity and Brodatz image set and our own Ancient shards image sets. The experiments results show the proposed method can integrate the texture features and color information to further improve distinguishing ability of each category images.
机译:提出了一种利用MGabor滤波器组从数字图像中提取纹理颜色特征,然后构造一组支持向量机(SVM)分类器对彩色数字图像进行自动准确分类的方法。成功的实验是在Simplicity和Brodatz影像集以及我们自己的Ancient shard影像集上进行的。实验结果表明,该方法能够融合纹理特征和颜色信息,进一步提高了分类图像的识别能力。

著录项

  • 来源
  • 会议地点 Chengdu(CN)
  • 作者单位

    School of Information Science and Technology, Northwest University, China Department of Electronic and Information Engineering, AnKang University, China;

    Department of Mathematics, AnKang University, Ankang, China;

    School of Information Science and Technology, Northwest University, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Image; Color; Texture; Classify; SVM;

    机译:图片;颜色;质地;分类;支持向量机;

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